#keras library

[ingoampt]

Day 13 _ What is Keras

Understanding Keras and Its Role in Deep Learning Understanding Keras and Its Role in Deep Learning What is Keras? Keras is an open-source software library that provides a Python interface for artificial neural networks. It serves as a high-level API, simplifying the process of building and training deep learning models. Developed by François Chollet, a researcher at Google, Keras was first…

[oldkamelle]

i keep coming across the tf2 acronym for tensorflow 2 and having to keep working normally like a horse with blinders on

[earlyspringtranscendence]

ik im talking a lot abt the books im reading rn (this is due to the fact that after eons of not having the time or energy i am once again reading books) but theydies i can happily announce that after 2 unsuccessful weapons and wielders books soulbrand has truly captured my enamoration once again i’m kissing keras lovingly and tenderly (the only way to kiss him)

[simlit]

Chosen of the Sun | | dawn // fifty-one

| @catamano | @keibea | @izayoiri | @thesimperiuscurse | @maladi777 | @poisonedsimmer | @amuhav | @sani-sims | @mangopysims | @rollingsim

next / previous / beginning

TALILA: What’s going on? This all seems very official… EVE: And worrisome. Kyrie, you look like you’ve seen a ghost. KYRIE: I’m just upset… No, I’m passed upset. EVE: It’ll be alright. We’ll get through it, whatever it is, but first you need to calm down. KYRIE: I’m trying. EVE: Deep breaths. KYRIE: Right. ÅSE: Enough of this. Stop smacking around tree. What is going to be done! TALILA: Has something happened? KYRIE: Please, everyone, sit down. KYRIE: I made a promise to you all to be honest. Admittedly, I don’t know all the details myself, but the truth is… I’m alone in this. I expect some of you still see me as part of this system, and I can’t fault you for it. But with things getting so difficult, I don’t know who else to turn to but the ten of you. I trust all of you more than anyone else. SARAYN: And him? Shouldn’t we be introduced to our mysterious twelfth? KYRIE: Everyone, this is Elion. He’s been assigned to my protection, and I can go nowhere without him. You see, before you all arrived here, my sister, Lady Alphanei Loren, was taken hostage by a vigilante group known as the Knights of Dawn. They are ransoming her life in return for the disbanding of the trials. A plan that won’t work for them while I still live. They’ve already made one attempt on my life. If Lord Tev’us hadn’t been with me that night, surely I’d already be dead. ÅSE: Mm… TALILA: How awful! But… how are we just now hearing of it? Why wouldn’t they want us to know? THERION: I expect they don’t want anyone to know. Stirring up confusion and fear makes for panic. Panic is hard to control. INDRYR: And they are all about control. EIRA: So what? If we sit here with our thumbs up our asses, they’ll just send more people to kill you. Does your Priestess think she can lock you— and us— up forever? KYRIE: Lucien is dead. This isn’t something they can contain. The entire city will be in chaos soon enough. EVE: Lucien is dead? But why? Who would kill him? INDRYR: That is the question. Considering everything, it would be naïve to think the two matters were not connected. ÅSE: He is innocent child! What cares he about knights and dawn? It is absurd! INDRYR: Yes, the child was almost certainly innocent. I expect it is more what he represented. ASTER: Well, don’t speak in riddles! Not all of us grew up in libraries, you know! KYRIE: Represents… Of course. EVE: Oh… Lucien’s mother… KYRIE: The Aravae offer enormous financial support to the church. Aside from the Eveydan Crown, they’re the main source of funding. Unbelievable. The Queen of Kera was the leading supporter for the Selenehelion’s reformation… SARAYN: Then they are not at all interested in compromise. Bloodsport or not, it seems they will stop at nothing to bring the ceremony down entirely. I expect they have very good reason. EIRA: Being angry about how a ceremony was conducted centuries ago doesn’t make a great case for slaughtering children. SARAYN: But it was not centuries ago. Those that have been robbed by these trials still live. To lose a love, a purpose… a King. No, I doubt they have forgotten. And I doubt less they shall forgive.

[haloinifio]

range

pertengahan tahun 2024, dimulai dengan ikhtiar menyambung silaturahmi sama temen-temen lama. sampe akhirnya ketemu satu perpustakaan di jakarta, yang setiap weekend selalu aku datengin cuma-cuma, cuma buat sekedar nyari tenang sebentar dari rutinitas melelahkan di kantor, atau sekedar baca buku dan pinjem beberapa bukunya untuk dibawa pulang (karna udah langganan member mereka untuk setahun hehe)

padahal perjalanan dari kos ke perpus cukup lama, bisa memakan waktu 2 jam naik transportasi umum. kadang telinga sengaja disumpel pake spotify biar lebih asik. tapi lately, jadi lebih suka diem dan mindful aja ngeliatin lingkungan sekitar. sesi observasi ini ternyata unik dan jadi bikin punya banyak pemikiran baru. yg seringkali bikin sedih, mikir dan bertanya ini dan itu, dan banyak kali bikin bersyukur.

————————————————————————————

pernah ketemu ibu-ibu yang nanya jalan dan akhirnya cerita segala macem soal anaknya yang kemudian bikin aku langsung pengen telfon mama di sore harinya

ngeliat kalo rasanya semua orang berusaha dengan keras, desek-desekan di transportasi umum kadang bikin bete karna panas dan sumpek, tapi kalo lagi rush hour rasanya kadang jadi punya energi lagi kalo “semua orang lagi berusaha” dan bikin mellow entah kenapa karna ngerasa diri sendiri lagi usaha juga kerja ngerantau jauh dari rumah

ikut volunteer dan ketemu temen-temen guru SLB yang selalu membagikan cerita mereka lewat story waktu ngajar anak-anak down syndrome. disadarkan kalo di luar sana banyak orang sabar luar biasa yg Allah amanahi buat ngasih harapan baru di hati kecil anak-anak itu. selalu amazed setiap denger ceritanya

ada banyak hal memorable yang ga bisa diungkapkan semuanya lewat tulisan

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tahun 2024 ditutup dengan 34 buku yang berhasil dibaca. tahun kemarin temanya tentang eksplorasi diri (mulai dari karir, level spiritual, dan ikhtiar cari jurusan yg paling cocok buat S2 nanti yg belum tau kapan bisa tercapai hehe). ikut beberapa kelas lewat instagram dan offline juga. semoga tahun ini bisa lebih banyak explore dan belajar.

tahun 2024 juga penuh dengan diri sendiri yg nyobain masak ini dan itu. buat trial catering dan juga buat coba-coba aja waktu udah jadi istri nanti (ceilah) blm tau kapan sih HAHAHA :(((((

tahun ini ingin mencoba hidup lebih mindful dan sehat lagi tapi versi indonesia aja. udah liat beberapa cuplikan dokter zaidul akbar dan obrolan podcast momscorner yang sangat aku suka——jadi menyimpulkan kalo Indonesia punya banyak sekali opsi makanan sehat. jadi tahun ini temanya pengen lebih belajar masak makanan yg super medok rempah Indonesia.

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sebagai salah satu orang yang menganggap spesialisasi itu keren, ada salah satu buku yg sangat aku suka. judulnya Range. buku ini nunjukin kalo dunia ini sangat general dan it will be super fun kalo kita jadiin diri kita sebagai orang yg general juga, bisa apa aja, belajar dan cobain apa aja

sampe akhirnya ngeconsider buat ambil master di bisnis, tapi masih harus nentuin skala prioritas dulu terkait uang, tempat dan waktunya hehe

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special mention buat foreword library. terima kasih udah selalu jadi tempat nyaman setiap minggunya untuk ngerasain tenang di tengah-tengah jakarta. tempat yang selalu aku nantikan di akhir minggu buat didatengin. tempat yang selalu aku nikmati perjalanan pulang dan perginya <3

[techaircraft]

Techaircraft

Dive into the world of Artificial Intelligence with Python! 🐍💡 Whether you're a seasoned coder or just starting, Python’s versatile libraries like Tensor Flow, Kera's, and sci-kit-learn make it easier than ever to build intelligent systems. 🤖 From developing predictive models to creating advanced neural networks, Python is your gateway to the future of technology. 📈🔍 Explore data analysis, natural language processing, and machine learning with hands-on projects that unlock endless possibilities. 🌐💻 Ready to level up your AI skills? Follow along for tutorials, tips, and inspiration to turn your innovative ideas into reality. . 𝐖𝐞𝐛𝐬𝐢𝐭𝐞 - www.techaircraft.com

𝐓𝐞𝐜𝐡𝐚𝐢𝐫𝐜𝐫𝐚𝐟𝐭 𝐬𝐮𝐩𝐩𝐨𝐫𝐭 𝐝𝐞𝐭𝐚𝐢𝐥𝐬:

𝐌𝐨𝐛𝐢𝐥𝐞 𝐍𝐮𝐦𝐛𝐞𝐫 - 8686069898

#ArtificialIntelligence#PythonProgramming#MachineLearning#DataScience#TechInnovation#NeuralNetworks#DeepLearning#CodingLife#PythonDeveloper#AIProjects#FutureOfTech#TechTrends#Programming#DataAnalysis#TensorFlow#Keras#ScikitLearn#LearnToCode#AICommunity#Innovation

[aibyrdidini]

PREDICTING WEATHER FORECAST FOR 30 DAYS IN AUGUST 2024 TO AVOID ACCIDENTS IN SANTA BARBARA, CALIFORNIA USING PYTHON, PARALLEL COMPUTING, AND AI LIBRARIES

Introduction

Weather forecasting is a crucial aspect of our daily lives, especially when it comes to avoiding accidents and ensuring public safety. In this article, we will explore the concept of predicting weather forecasts for 30 days in August 2024 to avoid accidents in Santa Barbara California using Python, parallel computing, and AI libraries. We will also discuss the concepts and definitions of the technologies involved and provide a step-by-step explanation of the code.

Concepts and Definitions

Parallel Computing: Parallel computing is a type of computation where many calculations or processes are carried out simultaneously. This approach can significantly speed up the processing time and is particularly useful for complex computations.

AI Libraries: AI libraries are pre-built libraries that provide functionalities for artificial intelligence and machine learning tasks. In this article, we will use libraries such as TensorFlow, Keras, and scikit-learn to build our weather forecasting model.

Weather Forecasting: Weather forecasting is the process of predicting the weather conditions for a specific region and time period. This involves analyzing various data sources such as temperature, humidity, wind speed, and atmospheric pressure.

Code Explanation

To predict the weather forecast for 30 days in August 2024, we will use a combination of parallel computing and AI libraries in Python. We will first import the necessary libraries and load the weather data for Santa Barbara, California.

import numpy as np

import pandas as pd

from sklearn.ensemble import RandomForestRegressor

from sklearn.model_selection import train_test_split

from tensorflow.keras.models import Sequential

from tensorflow.keras.layers import Dense

from joblib import Parallel, delayed

# Load weather data for Santa Barbara California

weather_data = pd.read_csv('Santa Barbara California_weather_data.csv')

Next, we will preprocess the data by converting the date column to a datetime format and extracting the relevant features

# Preprocess data

weather_data['date'] = pd.to_datetime(weather_data['date'])

weather_data['month'] = weather_data['date'].dt.month

weather_data['day'] = weather_data['date'].dt.day

weather_data['hour'] = weather_data['date'].dt.hour

# Extract relevant features

X = weather_data[['month', 'day', 'hour', 'temperature', 'humidity', 'wind_speed']]

y = weather_data['weather_condition']

We will then split the data into training and testing sets and build a random forest regressor model to predict the weather conditions.

# Split data into training and testing sets

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

# Build random forest regressor model

rf_model = RandomForestRegressor(n_estimators=100, random_state=42)

rf_model.fit(X_train, y_train)

To improve the accuracy of our model, we will use parallel computing to train multiple models with different hyperparameters and select the best-performing model.

# Define hyperparameter tuning function

def tune_hyperparameters(n_estimators, max_depth):

model = RandomForestRegressor(n_estimators=n_estimators, max_depth=max_depth, random_state=42)

model.fit(X_train, y_train)

return model.score(X_test, y_test)

# Use parallel computing to tune hyperparameters

results = Parallel(n_jobs=-1)(delayed(tune_hyperparameters)(n_estimators, max_depth) for n_estimators in [100, 200, 300] for max_depth in [None, 5, 10])

# Select best-performing model

best_model = rf_model

best_score = rf_model.score(X_test, y_test)

for result in results:

if result > best_score:

best_model = result

best_score = result

Finally, we will use the best-performing model to predict the weather conditions for the next 30 days in August 2024.

# Predict weather conditions for next 30 days

future_dates = pd.date_range(start='2024-09-01', end='2024-09-30')

future_data = pd.DataFrame({'month': future_dates.month, 'day': future_dates.day, 'hour': future_dates.hour})

future_data['weather_condition'] = best_model.predict(future_data)

Color Alerts

To represent the weather conditions, we will use a color alert system where:

Red represents severe weather conditions (e.g., heavy rain, strong winds)

Orange represents very bad weather conditions (e.g., thunderstorms, hail)

Yellow represents bad weather conditions (e.g., light rain, moderate winds)

Green represents good weather conditions (e.g., clear skies, calm winds)

We can use the following code to generate the color alerts:

# Define color alert function

def color_alert(weather_condition):

if weather_condition == 'severe':

return 'Red'

MY SECOND CODE SOLUTION PROPOSAL

We will use Python as our programming language and combine it with parallel computing and AI libraries to predict weather forecasts for 30 days in August 2024. We will use the following libraries:

OpenWeatherMap API: A popular API for retrieving weather data.

Scikit-learn: A machine learning library for building predictive models.

Dask: A parallel computing library for processing large datasets.

Matplotlib: A plotting library for visualizing data.

Here is the code:

```python

import pandas as pd

import numpy as np

from sklearn.ensemble import RandomForestRegressor

from sklearn.metrics import mean_squared_error

import dask.dataframe as dd

import matplotlib.pyplot as plt

import requests

# Load weather data from OpenWeatherMap API

url = "https://api.openweathermap.org/data/2.5/forecast?q=Santa Barbara California,US&units=metric&appid=YOUR_API_KEY"

response = requests.get(url)

weather_data = pd.json_normalize(response.json())

# Convert data to Dask DataFrame

weather_df = dd.from_pandas(weather_data, npartitions=4)

# Define a function to predict weather forecasts

def predict_weather(date, temperature, humidity):

# Use a random forest regressor to predict weather conditions

model = RandomForestRegressor(n_estimators=100, random_state=42)

model.fit(weather_df[["temperature", "humidity"]], weather_df["weather"])

prediction = model.predict([[temperature, humidity]])

return prediction

# Define a function to generate color-coded alerts

def generate_alerts(prediction):

if prediction > 80:

return "RED" # Severe weather condition

elif prediction > 60:

return "ORANGE" # Very bad weather condition

elif prediction > 40:

return "YELLOW" # Bad weather condition

else:

return "GREEN" # Good weather condition

# Predict weather forecasts for 30 days inAugust2024

predictions = []

for i in range(30):

date = f"2024-09-{i+1}"

temperature = weather_df["temperature"].mean()

humidity = weather_df["humidity"].mean()

prediction = predict_weather(date, temperature, humidity)

alerts = generate_alerts(prediction)

predictions.append((date, prediction, alerts))

# Visualize predictions using Matplotlib

plt.figure(figsize=(12, 6))

plt.plot([x[0] for x in predictions], [x[1] for x in predictions], marker="o")

plt.xlabel("Date")

plt.ylabel("Weather Prediction")

plt.title("Weather Forecast for 30 Days inAugust2024")

plt.show()

```

Explanation:

1. We load weather data from OpenWeatherMap API and convert it to a Dask DataFrame.

2. We define a function to predict weather forecasts using a random forest regressor.

3. We define a function to generate color-coded alerts based on the predicted weather conditions.

4. We predict weather forecasts for 30 days in August 2024 and generate color-coded alerts for each day.

5. We visualize the predictions using Matplotlib.

Conclusion:

In this article, we have demonstrated the power of parallel computing and AI libraries in predicting weather forecasts for 30 days in August 2024, specifically for Santa Barbara California. We have used TensorFlow, Keras, and scikit-learn on the first code and OpenWeatherMap API, Scikit-learn, Dask, and Matplotlib on the second code to build a comprehensive weather forecasting system. The color-coded alert system provides a visual representation of the severity of the weather conditions, enabling users to take necessary precautions to avoid accidents. This technology has the potential to revolutionize the field of weather forecasting, providing accurate and timely predictions to ensure public safety.

RDIDINI PROMPT ENGINEER

[asrisgratitudejournal]

Rejected

Yaampun terakhir nulis minggu lalu ya. Masih sangat hepi bahkan lagi diare pun ngapdet Tumblr. Tapi setelah hari Kamis itu, semua berubah. Aku lupa Jumat ngapain, kayanya ngelanjutina nyuci carius tubes. Terus Sabtu kelas 16 pagi, pengajian, baca di Gladstone Link terkait Islam di Indonesia (¿). I know ku anaknya emang random banget, kayanya Jumat malamnya juga nonton Balibo itu deh, atau itu Kamis malam ya lupa. Terus Minggu kelas 16 lagi (setelah kesiangan 1 jam karena ternyata BST berubah jadi DST), DILANJUT BACA EMAIL MASUK DECISION LETTER DARI G-CUBED YANG SUPER LAKNAT, lalu ngopi sama Ketua PPI Oxford baru terpilih di Opera. Pulang ngapain lupa. 

Langsung deh Senin kemarin pusing dan nangis aja si Asri nih. Paginya jam 9 ku email spv dan postdoc terkait paper yang ke-reject ini. Si postdoc langsung whatsapp ngajak ketemuan karena kayanya dia khawatir aja sih. Terus Bang Reybi juga ngajak ngopi karena malamnya ku tantrum dramatis di stori insta. Udah janjian kerja di library Exeter sama Puspa sebetulnya, tapi jadinya cuma makan Sasi’s aja sama dia. Pas di Opera sama Bang Reybi ku MENANGIS HUHU. Padahal beneran lagi BAHAS SAINS!!! Kaya Bang Reybi nanya “emangnya apa Non komennya?” terus pas recounting langsung BANJIR?! Kayanya karena ku belum sepenuhnya processing my emotion di hari Minggu itu. Ku gatau apakah ini aku sedih? Atau upset? Atau biasa aja? Kayanya pas hari Minggu lebih ke kesel sih dan mau “sok kuat” “gapapa kok yang kemarin kena reject pertama lebih menyedihkan Non”. Padahal nggak. Yang ini lebih menyedihkan karena ku betulan udah yang NGERAPIHIN BANGET dan BEKERJA SANGAT KERAS untuk resubmission ini. Bukan berarti yang versi pertama nggak bekerja keras ya, tapi lebih kayak… yang resubmission ini TUH UDAH BAGUS BANGET gitu loh (menurut aku, the author, tentu saja). Literally ku bisa bilang 10x lebih bagus dari first submission. TERUS AFTER ALL THOSE WORK masih aja ga nembus?  

Dan lebih ke frustrated aja sih. Betulan kaya jalan nabrak tembok aja terus. Setelah semua usaha. Kayak... YAALLAH kenapa sih.... Terus tapi setelah kemarin ngobrol sama postdoc dan dibales email juga sama spv semalam, bisa lebih lega karena bisa putting blame in other people aja HAHA yaitu: the editor. Emang beda ya, inilah pentingnya ngobrol sama orang yang sudah mengalami proses ini berkali-kali dan bahkan menjadi editor juga. Mereka ngejelasin gimana si editor jurnal ini super-problematik: nggak nyari 3rd reviewer (there are reasons why peer-reviewers itu minimal 3 dan jumlahnya ganjil), terus entah kenapa dari 2 reviews yang SUPER BEDA DECISIONNYA ini (satu decline dan satu accept with MINOR REVISION mind you) (dan yang nge-accept ini adalah orang yang juga ngereview first submission-ku, which means he knew how this manuscript has evolved BETTEr than the NEW Reviewer#2 yang super-mean), si editor decided to take the DECLINE recommendation? Kayak Bro, make your own decision juga?? That’s what you’re getting paid as an editor for??? Hhhhh. 

Terus ya setelah ngobrol sama postdoc juga, we agreed that si Reviewer#2 ini juga problematic dalam interpreting our words. Somehow dia ngambil kesimpulan sendiri aja gitu yang cukup jauh dan ekstrim dari apa yang kita tulis. Contoh: jelas-jelas nih ye, DI section 5.6. (yang dia suruh hapus karena “ABSURD. MANA ADA MULTIMILLION OIL COMPANIES WOULD MAKE THEIR DECISION BASED ON YOUR FINDING”), we didn’t FUCKING SAY ANYTHING ABOUT OIL COMPANIES SHOULD USE MY FINDING TO MAKE ANY DECISION WHATSOEVER??! Ku cuma bilang “OK, jadi dari study ini kemungkinan besar Hg di source rock gaakan ngefek ke produced hydrocarbon, avoiding the cost of extra-facilities for Hg removal”. JUJUR KURANG TONED-DOWN APA LAGI SIH ITU KALIMAT??! Harus di-spell out juga uncertainties-nya berapa??! Dan beneran ku bikin section ini (awalnya gaada di first submission) karena salah satu reviewer di first submission ngerasa “impact ni paper bisa di-explore lagi ke industry, ga cuma sains aja”. HHHHHHHHHHHHHH. APASIH. Haha jadi getting worked up lagi sekarang pas nulis ini. 

Anyway. Iya. Cukup lega dari kemarin udah ngobrol dengan banyak orang. Dari Bang Reybi yang super-practical & helpful & penuh solusi (karena coming from-nya adalah dari sincerity kayanya kasihan kali ya melihat aku sedih), sampe jadi ranting bareng postdoc dan spv yang emang lebih paham medan perangnya dan problem apa aja yang ada di peer-review system dan science publishing YANG SUPER MAHAL ini. Teman-teman di insta juga mungkin mau bantuin tapi karena kami datang dari dunia yang sangat berbeda agak susah ngasih support kaya gimana… tetap terima kasih banyak (emoji salim)… Ada juga teman sesama PhD yang mostly reply “WAH KEJAM BANGET REVIEWNYA” “Wah pedas sekali” à ini sangat validating bahwa bukan aku aja yang ngerasa itu komen sangat harsh…, terus teman-teman PhD lain yang sharing experience kena reject juga (making me realise bahwa I’m not alone experiencing ini)… teman-teman yang ga PhD juga shared dari experience mereka capek aja sama hidup in general, yang udah nyoba berkali-kali tetep ga berhasil juga. Iqbalpaz yang w tumpahin semua di chat dm insta & ngingetin buat booking konseling (salim). Yang sharing betapa helpfulnya konseling buat mereka… Yang nge-salut-in aku karena mau keluar dari comfort zone Indo buat ambil PhD ke Oxford… Pokoknya berbelas-belas replies itu betulan makasih banget banget banget. Just the fact that you guys took your time to READ MY POST (harus nge-pause dulu kan buat baca teks2 kecil itu), apalagi sampe nge-REPLY. Pokoknya semoga kebaikannya kembali ke kaliannn. 

Dah gitu dulu aja berterima kasih-nya. Tapi lesson learned-nya adalah: kalau buat diriku sendiri sepertinya memang harus bilang dan cerita ke luar kalau lagi sedih. Jauh lebih cepat leganya. Dulu awal-awal PhD (2021 awal), aku kalau frustrated terhadap sesuatu cuma di-bottled up aja, dan betulan ngilang. Ga apdet stori. Ga texting siapapun. Semuanya dipikirin sendiri. Ngeri deh. Kenapa ya,, apa karena ngerasa gaada safe space buat sharing ya. Dan masih ngerasa yang “ga enakan”, mikirnya “duh kalau gw ngepos gini apa nggak kaya orang ga bersyukur ya”. Setelah konseling pertama di 2022 sepertinya mindsetnya mulai berubah. Dan ya emang 2021 gapunya teman juga sih. Sekarang Alhamdulillah ada lah beberapa teman yang bisa dicurhatin. 

HHHHHH ALHAMDULILLAH. 

Terus ku juga mulai sekarang akan reach out ke teman-teman yang kelihatan dari postnya lagi sedih atau upset. Kalaupun gabisa bantu ngajak ngopi atau ngobrol banget, minimal nge-reply stori mereka aja validating what they’re feeling (apalagi kalau cewek ya yang sangat rentan blaming themselves, and feeling guilty, just for complaining misalnya), kadang kalau bisa ya ikut nganjing-nganjingin juga, dan letting them know aja that I’m here for them whenever they need me. 

Lah jadi panjang ni post. Dah gitu aja dulu. Ini mau pulang deh. 

VHL 16:17 31/10/2023 

[tech-insides]

Essential Skills for Aspiring Data Scientists in 2024

Welcome to another edition of Tech Insights! Today, we're diving into the essential skills that aspiring data scientists need to master in 2024. As the field of data science continues to evolve, staying updated with the latest skills and tools is crucial for success. Here are the key areas to focus on:

1. Programming Proficiency

Proficiency in programming languages like Python and R is foundational. Python, in particular, is widely used for data manipulation, analysis, and building machine learning models thanks to its rich ecosystem of libraries such as Pandas, NumPy, and Scikit-learn.

2. Statistical Analysis

A strong understanding of statistics is essential for data analysis and interpretation. Key concepts include probability distributions, hypothesis testing, and regression analysis, which help in making informed decisions based on data.

3. Machine Learning Mastery

Knowledge of machine learning algorithms and frameworks like TensorFlow, Keras, and PyTorch is critical. Understanding supervised and unsupervised learning, neural networks, and deep learning will set you apart in the field.

4. Data Wrangling Skills

The ability to clean, process, and transform data is crucial. Skills in using libraries like Pandas and tools like SQL for database management are highly valuable for preparing data for analysis.

5. Data Visualization

Effective communication of your findings through data visualization is important. Tools like Tableau, Power BI, and libraries like Matplotlib and Seaborn in Python can help you create impactful visualizations.

6. Big Data Technologies

Familiarity with big data tools like Hadoop, Spark, and NoSQL databases is beneficial, especially for handling large datasets. These tools help in processing and analyzing big data efficiently.

7. Domain Knowledge

Understanding the specific domain you are working in (e.g., finance, healthcare, e-commerce) can significantly enhance your analytical insights and make your solutions more relevant and impactful.

8. Soft Skills

Strong communication skills, problem-solving abilities, and teamwork are essential for collaborating with stakeholders and effectively conveying your findings.

Final Thoughts

The field of data science is ever-changing, and staying ahead requires continuous learning and adaptation. By focusing on these key skills, you'll be well-equipped to navigate the challenges and opportunities that 2024 brings.

If you're looking for more in-depth resources, tips, and articles on data science and machine learning, be sure to follow Tech Insights for regular updates. Let's continue to explore the fascinating world of technology together!

[dishachrista]

Exploring Game-Changing Applications: Your Easy Steps to Learn Machine Learning:

Machine learning technology has truly transformed multiple industries and continues to hold enormous potential for future development. If you're considering incorporating machine learning into your business or are simply eager to learn more about this transformative field, seeking advice from experts or enrolling in specialized courses is a wise step. For instance, the ACTE Institute offers comprehensive machine learning training programs that equip you with the knowledge and skills necessary for success in this rapidly evolving industry. Recognizing the potential of machine learning can unlock numerous avenues for data analysis, automation, and informed decision-making.

Now, let me share my successful journey in machine learning, which I believe can benefit everyone. These 10 steps have proven to be incredibly effective in helping me become a proficient machine learning practitioner:

Step 1: Understand the Basics

Develop a strong grasp of fundamental mathematics, particularly linear algebra, calculus, and statistics.

Learn a programming language like Python, which is widely used in machine learning and provides a variety of useful libraries.

Step 2: Learn Machine Learning Concepts

Enroll in online courses from reputable platforms like Coursera, edX, and Udemy. Notably, the ACTE machine learning course is a stellar choice, offering comprehensive education, job placement, and certification.

Supplement your learning with authoritative books such as "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron and "Pattern Recognition and Machine Learning" by Christopher Bishop.

Step 3: Hands-On Practice:

Dive into real-world projects using both simple and complex datasets. Practical experience is invaluable for gaining proficiency.

Participate in machine learning competitions on platforms like Kaggle to challenge yourself and learn from peers.

Step 4: Explore Advanced Topics

Delve into deep learning, a critical subset of machine learning that focuses on neural networks. Online resources like the Deep Learning Specialisation on Coursera are incredibly informative.

For those intrigued by language-related applications, explore Natural Language Processing (NLP) using resources like the "Natural Language Processing with Python" book by Steven Bird and Ewan Klein.

Step 5: Learn from the Community

Engage with online communities such as Reddit's r/Machine Learning and Stack Overflow. Participate in discussions, seek answers to queries, and absorb insights from others' experiences.

Follow machine learning blogs and podcasts to stay updated on the latest advancements, case studies, and best practices.

Step 6: Implement Advanced Projects

Challenge yourself with intricate projects that stretch your skills. This might involve tasks like image recognition, building recommendation systems, or even crafting your own AI-powered application.

Step 7: Stay updated

Stay current by reading research papers from renowned conferences like NeurIPS, ICML, and CVPR to stay on top of cutting-edge techniques.

Consider advanced online courses that delve into specialized topics such as reinforcement learning and generative adversarial networks (GANs).

Step 8: Build a Portfolio

Showcase your completed projects on GitHub to demonstrate your expertise to potential employers or collaborators.

Step 9: Network and Explore Career Opportunities

Attend conferences, workshops, and meetups to network with industry professionals and stay connected with the latest trends.

Explore job opportunities in data science and machine learning, leveraging your portfolio and projects to stand out during interviews.

In essence, mastering machine learning involves a step-by-step process encompassing learning core concepts, engaging in hands-on practice, and actively participating in the vibrant machine learning community. Starting from foundational mathematics and programming, progressing through online courses and projects, and eventually venturing into advanced topics like deep learning, this journey equips you with essential skills. Embracing the machine learning community and building a robust portfolio opens doors to promising opportunities in this dynamic and impactful field.

[learnershub101]

25 Udemy Paid Courses for Free with Certification (Only for Limited Time)

2023 Complete SQL Bootcamp from Zero to Hero in SQL

Become an expert in SQL by learning through concept & Hands-on coding :)

What you'll learn

Use SQL to query a database Be comfortable putting SQL on their resume Replicate real-world situations and query reports Use SQL to perform data analysis Learn to perform GROUP BY statements Model real-world data and generate reports using SQL Learn Oracle SQL by Professionally Designed Content Step by Step! Solve any SQL-related Problems by Yourself Creating Analytical Solutions! Write, Read and Analyze Any SQL Queries Easily and Learn How to Play with Data! Become a Job-Ready SQL Developer by Learning All the Skills You will Need! Write complex SQL statements to query the database and gain critical insight on data Transition from the Very Basics to a Point Where You can Effortlessly Work with Large SQL Queries Learn Advanced Querying Techniques Understand the difference between the INNER JOIN, LEFT/RIGHT OUTER JOIN, and FULL OUTER JOIN Complete SQL statements that use aggregate functions Using joins, return columns from multiple tables in the same query

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Python Programming Complete Beginners Course Bootcamp 2023

2023 Complete Python Bootcamp || Python Beginners to advanced || Python Master Class || Mega Course

What you'll learn

Basics in Python programming Control structures, Containers, Functions & Modules OOPS in Python How python is used in the Space Sciences Working with lists in python Working with strings in python Application of Python in Mars Rovers sent by NASA

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Learn PHP and MySQL for Web Application and Web Development

Unlock the Power of PHP and MySQL: Level Up Your Web Development Skills Today

What you'll learn

Use of PHP Function Use of PHP Variables Use of MySql Use of Database

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T-Shirt Design for Beginner to Advanced with Adobe Photoshop

Unleash Your Creativity: Master T-Shirt Design from Beginner to Advanced with Adobe Photoshop

What you'll learn

Function of Adobe Photoshop Tools of Adobe Photoshop T-Shirt Design Fundamentals T-Shirt Design Projects

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Complete Data Science BootCamp

Learn about Data Science, Machine Learning and Deep Learning and build 5 different projects.

What you'll learn

Learn about Libraries like Pandas and Numpy which are heavily used in Data Science. Build Impactful visualizations and charts using Matplotlib and Seaborn. Learn about Machine Learning LifeCycle and different ML algorithms and their implementation in sklearn. Learn about Deep Learning and Neural Networks with TensorFlow and Keras Build 5 complete projects based on the concepts covered in the course.

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Essentials User Experience Design Adobe XD UI UX Design

Learn UI Design, User Interface, User Experience design, UX design & Web Design

What you'll learn

How to become a UX designer Become a UI designer Full website design All the techniques used by UX professionals

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Build a Custom E-Commerce Site in React + JavaScript Basics

Build a Fully Customized E-Commerce Site with Product Categories, Shopping Cart, and Checkout Page in React.

What you'll learn

Introduction to the Document Object Model (DOM) The Foundations of JavaScript JavaScript Arithmetic Operations Working with Arrays, Functions, and Loops in JavaScript JavaScript Variables, Events, and Objects JavaScript Hands-On - Build a Photo Gallery and Background Color Changer Foundations of React How to Scaffold an Existing React Project Introduction to JSON Server Styling an E-Commerce Store in React and Building out the Shop Categories Introduction to Fetch API and React Router The concept of "Context" in React Building a Search Feature in React Validating Forms in React

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Complete Bootstrap & React Bootcamp with Hands-On Projects

Learn to Build Responsive, Interactive Web Apps using Bootstrap and React.

What you'll learn

Learn the Bootstrap Grid System Learn to work with Bootstrap Three Column Layouts Learn to Build Bootstrap Navigation Components Learn to Style Images using Bootstrap Build Advanced, Responsive Menus using Bootstrap Build Stunning Layouts using Bootstrap Themes Learn the Foundations of React Work with JSX, and Functional Components in React Build a Calculator in React Learn the React State Hook Debug React Projects Learn to Style React Components Build a Single and Multi-Player Connect-4 Clone with AI Learn React Lifecycle Events Learn React Conditional Rendering Build a Fully Custom E-Commerce Site in React Learn the Foundations of JSON Server Work with React Router

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Build an Amazon Affiliate E-Commerce Store from Scratch

Earn Passive Income by Building an Amazon Affiliate E-Commerce Store using WordPress, WooCommerce, WooZone, & Elementor

What you'll learn

Registering a Domain Name & Setting up Hosting Installing WordPress CMS on Your Hosting Account Navigating the WordPress Interface The Advantages of WordPress Securing a WordPress Installation with an SSL Certificate Installing Custom Themes for WordPress Installing WooCommerce, Elementor, & WooZone Plugins Creating an Amazon Affiliate Account Importing Products from Amazon to an E-Commerce Store using WooZone Plugin Building a Customized Shop with Menu's, Headers, Branding, & Sidebars Building WordPress Pages, such as Blogs, About Pages, and Contact Us Forms Customizing Product Pages on a WordPress Power E-Commerce Site Generating Traffic and Sales for Your Newly Published Amazon Affiliate Store

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The Complete Beginner Course to Optimizing ChatGPT for Work

Learn how to make the most of ChatGPT's capabilities in efficiently aiding you with your tasks.

What you'll learn

Learn how to harness ChatGPT's functionalities to efficiently assist you in various tasks, maximizing productivity and effectiveness. Delve into the captivating fusion of product development and SEO, discovering effective strategies to identify challenges, create innovative tools, and expertly Understand how ChatGPT is a technological leap, akin to the impact of iconic tools like Photoshop and Excel, and how it can revolutionize work methodologies thr Showcase your learning by creating a transformative project, optimizing your approach to work by identifying tasks that can be streamlined with artificial intel

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AWS, JavaScript, React | Deploy Web Apps on the Cloud

Cloud Computing | Linux Foundations | LAMP Stack | DBMS | Apache | NGINX | AWS IAM | Amazon EC2 | JavaScript | React

What you'll learn

Foundations of Cloud Computing on AWS and Linode Cloud Computing Service Models (IaaS, PaaS, SaaS) Deploying and Configuring a Virtual Instance on Linode and AWS Secure Remote Administration for Virtual Instances using SSH Working with SSH Key Pair Authentication The Foundations of Linux (Maintenance, Directory Commands, User Accounts, Filesystem) The Foundations of Web Servers (NGINX vs Apache) Foundations of Databases (SQL vs NoSQL), Database Transaction Standards (ACID vs CAP) Key Terminology for Full Stack Development and Cloud Administration Installing and Configuring LAMP Stack on Ubuntu (Linux, Apache, MariaDB, PHP) Server Security Foundations (Network vs Hosted Firewalls). Horizontal and Vertical Scaling of a virtual instance on Linode using NodeBalancers Creating Manual and Automated Server Images and Backups on Linode Understanding the Cloud Computing Phenomenon as Applicable to AWS The Characteristics of Cloud Computing as Applicable to AWS Cloud Deployment Models (Private, Community, Hybrid, VPC) Foundations of AWS (Registration, Global vs Regional Services, Billing Alerts, MFA) AWS Identity and Access Management (Mechanics, Users, Groups, Policies, Roles) Amazon Elastic Compute Cloud (EC2) - (AMIs, EC2 Users, Deployment, Elastic IP, Security Groups, Remote Admin) Foundations of the Document Object Model (DOM) Manipulating the DOM Foundations of JavaScript Coding (Variables, Objects, Functions, Loops, Arrays, Events) Foundations of ReactJS (Code Pen, JSX, Components, Props, Events, State Hook, Debugging) Intermediate React (Passing Props, Destrcuting, Styling, Key Property, AI, Conditional Rendering, Deployment) Building a Fully Customized E-Commerce Site in React Intermediate React Concepts (JSON Server, Fetch API, React Router, Styled Components, Refactoring, UseContext Hook, UseReducer, Form Validation)

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Run Multiple Sites on a Cloud Server: AWS & Digital Ocean

Server Deployment | Apache Configuration | MySQL | PHP | Virtual Hosts | NS Records | DNS | AWS Foundations | EC2

What you'll learn

A solid understanding of the fundamentals of remote server deployment and configuration, including network configuration and security. The ability to install and configure the LAMP stack, including the Apache web server, MySQL database server, and PHP scripting language. Expertise in hosting multiple domains on one virtual server, including setting up virtual hosts and managing domain names. Proficiency in virtual host file configuration, including creating and configuring virtual host files and understanding various directives and parameters. Mastery in DNS zone file configuration, including creating and managing DNS zone files and understanding various record types and their uses. A thorough understanding of AWS foundations, including the AWS global infrastructure, key AWS services, and features. A deep understanding of Amazon Elastic Compute Cloud (EC2) foundations, including creating and managing instances, configuring security groups, and networking. The ability to troubleshoot common issues related to remote server deployment, LAMP stack installation and configuration, virtual host file configuration, and D An understanding of best practices for remote server deployment and configuration, including security considerations and optimization for performance. Practical experience in working with remote servers and cloud-based solutions through hands-on labs and exercises. The ability to apply the knowledge gained from the course to real-world scenarios and challenges faced in the field of web hosting and cloud computing. A competitive edge in the job market, with the ability to pursue career opportunities in web hosting and cloud computing.

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Cloud-Powered Web App Development with AWS and PHP

AWS Foundations | IAM | Amazon EC2 | Load Balancing | Auto-Scaling Groups | Route 53 | PHP | MySQL | App Deployment

What you'll learn

Understanding of cloud computing and Amazon Web Services (AWS) Proficiency in creating and configuring AWS accounts and environments Knowledge of AWS pricing and billing models Mastery of Identity and Access Management (IAM) policies and permissions Ability to launch and configure Elastic Compute Cloud (EC2) instances Familiarity with security groups, key pairs, and Elastic IP addresses Competency in using AWS storage services, such as Elastic Block Store (EBS) and Simple Storage Service (S3) Expertise in creating and using Elastic Load Balancers (ELB) and Auto Scaling Groups (ASG) for load balancing and scaling web applications Knowledge of DNS management using Route 53 Proficiency in PHP programming language fundamentals Ability to interact with databases using PHP and execute SQL queries Understanding of PHP security best practices, including SQL injection prevention and user authentication Ability to design and implement a database schema for a web application Mastery of PHP scripting to interact with a database and implement user authentication using sessions and cookies Competency in creating a simple blog interface using HTML and CSS and protecting the blog content using PHP authentication. Students will gain practical experience in creating and deploying a member-only blog with user authentication using PHP and MySQL on AWS.

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CSS, Bootstrap, JavaScript And PHP Stack Complete Course

CSS, Bootstrap And JavaScript And PHP Complete Frontend and Backend Course

What you'll learn

Introduction to Frontend and Backend technologies Introduction to CSS, Bootstrap And JavaScript concepts, PHP Programming Language Practically Getting Started With CSS Styles, CSS 2D Transform, CSS 3D Transform Bootstrap Crash course with bootstrap concepts Bootstrap Grid system,Forms, Badges And Alerts Getting Started With Javascript Variables,Values and Data Types, Operators and Operands Write JavaScript scripts and Gain knowledge in regard to general javaScript programming concepts PHP Section Introduction to PHP, Various Operator types , PHP Arrays, PHP Conditional statements Getting Started with PHP Function Statements And PHP Decision Making PHP 7 concepts PHP CSPRNG And PHP Scalar Declaration

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Learn HTML - For Beginners

Lean how to create web pages using HTML

What you'll learn

How to Code in HTML Structure of an HTML Page Text Formatting in HTML Embedding Videos Creating Links Anchor Tags Tables & Nested Tables Building Forms Embedding Iframes Inserting Images

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Learn Bootstrap - For Beginners

Learn to create mobile-responsive web pages using Bootstrap

What you'll learn

Bootstrap Page Structure Bootstrap Grid System Bootstrap Layouts Bootstrap Typography Styling Images Bootstrap Tables, Buttons, Badges, & Progress Bars Bootstrap Pagination Bootstrap Panels Bootstrap Menus & Navigation Bars Bootstrap Carousel & Modals Bootstrap Scrollspy Bootstrap Themes

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JavaScript, Bootstrap, & PHP - Certification for Beginners

A Comprehensive Guide for Beginners interested in learning JavaScript, Bootstrap, & PHP

What you'll learn

Master Client-Side and Server-Side Interactivity using JavaScript, Bootstrap, & PHP Learn to create mobile responsive webpages using Bootstrap Learn to create client and server-side validated input forms Learn to interact with a MySQL Database using PHP

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Linode: Build and Deploy Responsive Websites on the Cloud

Cloud Computing | IaaS | Linux Foundations | Apache + DBMS | LAMP Stack | Server Security | Backups | HTML | CSS

What you'll learn

Understand the fundamental concepts and benefits of Cloud Computing and its service models. Learn how to create, configure, and manage virtual servers in the cloud using Linode. Understand the basic concepts of Linux operating system, including file system structure, command-line interface, and basic Linux commands. Learn how to manage users and permissions, configure network settings, and use package managers in Linux. Learn about the basic concepts of web servers, including Apache and Nginx, and databases such as MySQL and MariaDB. Learn how to install and configure web servers and databases on Linux servers. Learn how to install and configure LAMP stack to set up a web server and database for hosting dynamic websites and web applications. Understand server security concepts such as firewalls, access control, and SSL certificates. Learn how to secure servers using firewalls, manage user access, and configure SSL certificates for secure communication. Learn how to scale servers to handle increasing traffic and load. Learn about load balancing, clustering, and auto-scaling techniques. Learn how to create and manage server images. Understand the basic structure and syntax of HTML, including tags, attributes, and elements. Understand how to apply CSS styles to HTML elements, create layouts, and use CSS frameworks.

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PHP & MySQL - Certification Course for Beginners

Learn to Build Database Driven Web Applications using PHP & MySQL

What you'll learn

PHP Variables, Syntax, Variable Scope, Keywords Echo vs. Print and Data Output PHP Strings, Constants, Operators PHP Conditional Statements PHP Elseif, Switch, Statements PHP Loops - While, For PHP Functions PHP Arrays, Multidimensional Arrays, Sorting Arrays Working with Forms - Post vs. Get PHP Server Side - Form Validation Creating MySQL Databases Database Administration with PhpMyAdmin Administering Database Users, and Defining User Roles SQL Statements - Select, Where, And, Or, Insert, Get Last ID MySQL Prepared Statements and Multiple Record Insertion PHP Isset MySQL - Updating Records

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Linode: Deploy Scalable React Web Apps on the Cloud

Cloud Computing | IaaS | Server Configuration | Linux Foundations | Database Servers | LAMP Stack | Server Security

What you'll learn

Introduction to Cloud Computing Cloud Computing Service Models (IaaS, PaaS, SaaS) Cloud Server Deployment and Configuration (TFA, SSH) Linux Foundations (File System, Commands, User Accounts) Web Server Foundations (NGINX vs Apache, SQL vs NoSQL, Key Terms) LAMP Stack Installation and Configuration (Linux, Apache, MariaDB, PHP) Server Security (Software & Hardware Firewall Configuration) Server Scaling (Vertical vs Horizontal Scaling, IP Swaps, Load Balancers) React Foundations (Setup) Building a Calculator in React (Code Pen, JSX, Components, Props, Events, State Hook) Building a Connect-4 Clone in React (Passing Arguments, Styling, Callbacks, Key Property) Building an E-Commerce Site in React (JSON Server, Fetch API, Refactoring)

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Internet and Web Development Fundamentals

Learn how the Internet Works and Setup a Testing & Production Web Server

What you'll learn

How the Internet Works Internet Protocols (HTTP, HTTPS, SMTP) The Web Development Process Planning a Web Application Types of Web Hosting (Shared, Dedicated, VPS, Cloud) Domain Name Registration and Administration Nameserver Configuration Deploying a Testing Server using WAMP & MAMP Deploying a Production Server on Linode, Digital Ocean, or AWS Executing Server Commands through a Command Console Server Configuration on Ubuntu Remote Desktop Connection and VNC SSH Server Authentication FTP Client Installation FTP Uploading

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Linode: Web Server and Database Foundations

Cloud Computing | Instance Deployment and Config | Apache | NGINX | Database Management Systems (DBMS)

What you'll learn

Introduction to Cloud Computing (Cloud Service Models) Navigating the Linode Cloud Interface Remote Administration using PuTTY, Terminal, SSH Foundations of Web Servers (Apache vs. NGINX) SQL vs NoSQL Databases Database Transaction Standards (ACID vs. CAP Theorem) Key Terms relevant to Cloud Computing, Web Servers, and Database Systems

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Java Training Complete Course 2022

Learn Java Programming language with Java Complete Training Course 2022 for Beginners

What you'll learn

You will learn how to write a complete Java program that takes user input, processes and outputs the results You will learn OOPS concepts in Java You will learn java concepts such as console output, Java Variables and Data Types, Java Operators And more You will be able to use Java for Selenium in testing and development

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Learn To Create AI Assistant (JARVIS) With Python

How To Create AI Assistant (JARVIS) With Python Like the One from Marvel's Iron Man Movie

What you'll learn

how to create an personalized artificial intelligence assistant how to create JARVIS AI how to create ai assistant

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Keyword Research, Free Backlinks, Improve SEO -Long Tail Pro

LongTailPro is the keyword research service we at Coursenvy use for ALL our clients! In this course, find SEO keywords,

What you'll learn

Learn everything Long Tail Pro has to offer from A to Z! Optimize keywords in your page/post titles, meta descriptions, social media bios, article content, and more! Create content that caters to the NEW Search Engine Algorithms and find endless keywords to rank for in ALL the search engines! Learn how to use ALL of the top-rated Keyword Research software online! Master analyzing your COMPETITIONS Keywords! Get High-Quality Backlinks that will ACTUALLY Help your Page Rank!

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[seashoresolutions]

The Power of Python: How Python Development Services Transform Businesses

In the rapidly evolving landscape of technology, businesses are continuously seeking innovative solutions to gain a competitive edge. Python, a versatile and powerful programming language, has emerged as a game-changer for enterprises worldwide. Its simplicity, efficiency, and vast ecosystem of libraries have made Python development services a catalyst for transformation. In this blog, we will explore the significant impact Python has on businesses and how it can revolutionize their operations.

Python's Versatility:

Python's versatility is one of its key strengths, enabling businesses to leverage it for a wide range of applications. From web development to data analysis, artificial intelligence to automation, Python can handle diverse tasks with ease. This adaptability allows businesses to streamline their processes, improve productivity, and explore new avenues for growth.

Rapid Development and Time-to-Market:

Python's clear and concise syntax accelerates the development process, reducing the time to market products and services. With Python, developers can create robust applications in a shorter timeframe compared to other programming languages. This agility is especially crucial in fast-paced industries where staying ahead of the competition is essential.

Cost-Effectiveness:

Python's open-source nature eliminates the need for expensive licensing fees, making it a cost-effective choice for businesses. Moreover, the availability of a vast and active community of Python developers ensures that businesses can find affordable expertise for their projects. This cost-efficiency is particularly advantageous for startups and small to medium-sized enterprises.

Data Analysis and Insights:

In the era of big data, deriving valuable insights from vast datasets is paramount for making informed business decisions. Python's libraries like NumPy, Pandas, and Matplotlib provide powerful tools for data manipulation, analysis, and visualization. Python's data processing capabilities empower businesses to uncover patterns, trends, and actionable insights from their data, leading to data-driven strategies and increased efficiency.

Web Development and Scalability:

Python's simplicity and robust frameworks like Django and Flask have made it a popular choice for web development. Python-based web applications are known for their scalability, allowing businesses to handle growing user demands without compromising performance. This scalability ensures a seamless user experience, even during peak traffic periods.

Machine Learning and Artificial Intelligence:

Python's dominance in the field of artificial intelligence and machine learning is undeniable. Libraries like TensorFlow, Keras, and PyTorch have made it easier for businesses to implement sophisticated machine learning algorithms into their processes. With Python, businesses can harness the power of AI to automate tasks, predict trends, optimize processes, and personalize user experiences.

Automation and Efficiency:

Python's versatility extends to automation, making it an ideal choice for streamlining repetitive tasks. From automating data entry and report generation to managing workflows, Python development services can help businesses save time and resources, allowing employees to focus on more strategic initiatives.

Integration and Interoperability:

Many businesses have existing systems and technologies in place. Python's seamless integration capabilities allow it to work in harmony with various platforms and technologies. This interoperability simplifies the process of integrating Python solutions into existing infrastructures, preventing disruptions and reducing implementation complexities.

Security and Reliability:

Python's strong security features and active community support contribute to its reliability as a programming language. Businesses can rely on Python development services to build secure applications that protect sensitive data and guard against potential cyber threats.

Conclusion:

Python's rising popularity in the business world is a testament to its transformative power. From enhancing development speed and reducing costs to enabling data-driven decisions and automating processes, Python development services have revolutionized the way businesses operate. Embracing Python empowers enterprises to stay ahead in an ever-changing technological landscape and achieve sustainable growth in the digital era. Whether you're a startup or an established corporation, harnessing the potential of Python can unlock a world of possibilities and take your business to new heights.

[internsipgate]

How to Start a Career in Artificial Intelligence: A Comprehensive Guide

Artificial Intelligence (AI) is transforming industries, creating job opportunities, and shaping the future of technology. If you're intrigued by the idea of machines learning and making decisions, starting a career in AI might be the right path for you. This guide will provide actionable steps to help you kickstart your journey into the world of AI.https://internshipgate.com

Step 1: Understand the Basics of AI

Before diving into AI as a career, it's essential to understand what AI is and how it works. AI involves creating systems capable of performing tasks that typically require human intelligence, such as:

Machine Learning (ML): Algorithms that improve through experience.

Natural Language Processing (NLP): Enabling machines to understand and respond to human language.

Computer Vision: Allowing machines to interpret and analyze visual data.

Robotics: Designing intelligent robots for various tasks.

Start by exploring free resources like online articles, videos, and introductory courses to build a foundational understanding of AI concepts.

Step 2: Learn the Necessary Skills

AI professionals need a strong foundation in several disciplines. Focus on acquiring the following skills:

Mathematics and Statistics

AI relies heavily on linear algebra, calculus, probability, and statistics. Strengthen your math skills through courses or self-study.

Programming

Proficiency in programming languages like Python, R, or Java is crucial. Python, in particular, is widely used in AI due to its libraries like TensorFlow, PyTorch, and Scikit-learn.

Data Analysis and Visualization

Understand how to work with large datasets, clean data, and visualize insights. Tools like Pandas, NumPy, and Matplotlib are helpful for this.

Machine Learning and Deep Learning

Dive into ML and deep learning concepts by working with algorithms, neural networks, and frameworks like Keras or TensorFlow.

Domain Knowledge

Understanding the industry where you want to apply AI (e.g., healthcare, finance, or marketing) is beneficial.

Step 3: Pursue Education and Certifications

While a formal degree in computer science, data science, or AI can be advantageous, it's not mandatory. Many professionals transition into AI with certifications and online courses.

Popular Platforms for Learning AI:

Coursera: Offers courses like Andrew Ng’s Machine Learning and AI for Everyone.

edX: Features AI programs from institutions like MIT and Harvard.

Udemy: Affordable and beginner-friendly AI tutorials.

Certifications to Consider:

Google AI Certification

IBM AI Engineering Professional Certificate

Microsoft Certified: Azure AI Engineer Associate

Step 4: Gain Practical Experience

Hands-on experience is key to mastering AI. Here’s how you can get started:

Projects: Build AI models using datasets from platforms like Kaggle or UCI Machine Learning Repository.

Internships: Apply for AI internships to gain real-world exposure.

Hackathons: Participate in AI and ML hackathons to challenge yourself and network with professionals.

Step 5: Build a Strong Portfolio

Showcase your AI skills by creating an impressive portfolio. Include:

Projects you���ve worked on, with detailed descriptions and outcomes.

GitHub repositories featuring your AI code.

Documentation or blogs explaining your AI models and findings.

Step 6: Network and Stay Updated

AI is a fast-evolving field. Stay current by:

Attending AI conferences like NeurIPS, ICML, or CVPR.

Joining AI communities on LinkedIn, Reddit, or Slack.

Following industry leaders and trends.

Networking can open doors to mentorships, collaborations, and job opportunities.

Step 7: Apply for AI Roles

Start applying for entry-level AI positions like:

AI Engineer

Data Scientist

Machine Learning Engineer

NLP Specialist

Tailor your resume to highlight relevant skills and projects. Use platforms like LinkedIn, Indeed, and niche AI job boards to find opportunities.

Conclusion

Starting a career in AI requires dedication, continuous learning, and practical experience. By building a strong foundation, acquiring relevant skills, and staying proactive, you can carve a successful path in this exciting field.

Remember, the journey might seem challenging, but with determination and the right resources, you can achieve your goals in AI. 🚀https://internshipgate.com

[styrishai295]

Unlock the Power of Artificial Intelligence with Our Comprehensive Course

What is Artificial Intelligence (AI)?

Artificial Intelligence is a branch of computer science that focuses on creating intelligent machines that can perform tasks that typically require human intelligence, such as learning, problem-solving, and decision-making. AI has many applications in various industries, including healthcare, ai tutorial for beginners finance, transportation, and customer service.

What is Deep Learning?

Deep Learning is a subset of AI that uses neural networks with multiple layers to learn complex patterns in data. It is inspired by the structure and function of the human brain and is particularly useful for image and speech recognition, natural language processing, and predictive analytics.

Benefits of Learning AI and Deep Learning

Learning AI and Deep Learning can open up many career opportunities in the tech industry, including:

Data Scientist: With the increasing amount of data being generated every day, artificial intelligence course companies need professionals who can collect, analyze, and interpret data to make informed decisions.

Machine Learning Engineer: As AI becomes more prevalent, the demand for machine learning engineers who can design and develop intelligent systems is on the rise.

AI Researcher: As AI continues to advance, researchers are needed to push the boundaries of what is possible with AI.

Getting Started with AI and Deep Learning

To get started with AI and Deep Learning, you will need to learn programming languages such as Python and R, as well as libraries like TensorFlow and Keras. deep learning course Online You will also need to have a basic understanding of linear algebra, calculus, and probability.

Online Courses for Learning AI and Deep Learning

There are many online courses available that can help you learn AI and Deep Learning. Some popular options include:

Deep AI Learning Course: This course covers the basics of deep learning, including neural networks, convolutional neural networks, deep ai learning course and recurrent neural networks.

Artificial Intelligence Course: This course covers the basics of artificial intelligence, including machine learning, natural language processing, and computer vision.

Deep Learning Tutorial for Beginners: This tutorial provides a comprehensive introduction to deep learning, including the basics of neural networks and how to implement them using Python and TensorFlow.

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"Semi-Supervised Learning for Image Classification: A Practical Example with Keras"

Introduction Semi-supervised learning for image classification is a powerful technique used to improve the accuracy of image classification models by leveraging both labeled and unlabeled data. This tutorial will provide a comprehensive guide on how to implement semi-supervised learning for image classification using the Keras deep learning library. What Readers Will Learn The fundamentals of…

[educationtech]

What Is The Role of Python in Artificial Intelligence? - Arya College

Importance of Python in AI

Arya College of Engineering & I.T. has many courses for Python which has become the dominant programming language in the fields of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) due to several compelling factors:

1. Simplicity and Readability

Python's syntax is clear and intuitive, making it accessible for both beginners and experienced developers. This simplicity allows for rapid prototyping and experimentation, essential in AI development where iterative testing is common. The ease of learning Python enables new practitioners to focus on algorithms and data rather than getting bogged down by complex syntax.

2. Extensive Libraries and Frameworks

Python boasts a rich ecosystem of libraries specifically designed for AI and ML tasks. Libraries such as TensorFlow, Keras, PyTorch, sci-kit-learn, NumPy, and Pandas provide pre-built functions that facilitate complex computations, data manipulation, and model training. This extensive support reduces development time significantly, allowing developers to focus on building models rather than coding from scratch.

3. Strong Community Support

The active Python community contributes to its popularity by providing a wealth of resources, tutorials, and forums for troubleshooting. This collaborative environment fosters learning and problem-solving, which is particularly beneficial for newcomers to AI. Community support also means that developers can easily find help when encountering challenges during their projects.

4. Versatility Across Applications

Python is versatile enough to be used in various applications beyond AI, including web development, data analysis, automation, and more. This versatility makes it a valuable skill for developers who may want to branch into different areas of technology. In AI specifically, Python can handle tasks ranging from data preprocessing to deploying machine learning models.

5. Data Handling Capabilities

Python excels at data handling and processing, which are crucial in AI projects. Libraries like Pandas and NumPy allow efficient manipulation of large datasets, while tools like Matplotlib and Seaborn facilitate data visualization. The ability to preprocess data effectively ensures that models are trained on high-quality inputs, leading to better performance.

6. Integration with Other Technologies

Python integrates well with other languages and technologies, making it suitable for diverse workflows in AI projects. It can work alongside big data tools like Apache Spark or Hadoop, enhancing its capabilities in handling large-scale datasets. This interoperability is vital as AI applications often require the processing of vast amounts of data from various sources.

How to Learn Python for AI

Learning Python effectively requires a structured approach that focuses on both the language itself and its application in AI:

1. Start with the Basics

Begin by understanding Python's syntax and basic programming concepts:

Data types: Learn about strings, lists, tuples, dictionaries.

Control structures: Familiarize yourself with loops (for/while) and conditionals (if/else).

Functions: Understand how to define and call functions.

2. Explore Key Libraries

Once comfortable with the basics, delve into libraries essential for AI:

NumPy: For numerical computations.

Pandas: For data manipulation and analysis.

Matplotlib/Seaborn: For data visualization.

TensorFlow/Keras/PyTorch: For building machine learning models.

3. Practical Projects

Apply your knowledge through hands-on projects:

Start with simple projects like linear regression or classification tasks using datasets from platforms like Kaggle.

Gradually move to more complex projects involving neural networks or natural language processing.

4. Online Courses and Resources

Utilize online platforms that offer structured courses:

Websites like Coursera, edX, or Udacity provide courses specifically focused on Python for AI/ML.

YouTube channels dedicated to programming can also be valuable resources.

5. Engage with the Community

Join forums like Stack Overflow or Reddit communities focused on Python and AI:

Participate in discussions or seek help when needed.

Collaborate on open-source projects or contribute to GitHub repositories related to AI.

6. Continuous Learning

AI is a rapidly evolving field; therefore:

Stay updated with the latest trends by following relevant blogs or research papers.

Attend workshops or webinars focusing on advancements in AI technologies.

By following this structured approach, you can build a solid foundation in Python that will serve you well in your journey into artificial intelligence and machine learning.