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#best data annotation companies
maruful009 · 6 months
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Hello @Everyone Marufu Islam excels in data labelling for startups and businesses of all sizes, using tools like Supervisely, Super Annotate, Labelbox, CVAT, and more. Fluent in COCO, XML, JSON, and CSV formats. Ready to enhance your projects? Everyone please check the gig and let me know if there is anything wrong https://www.fiverr.com/s/lP63gy @everyone Fiveer And Upwork Community Group Link https://discord.gg/VsVGKYwA Please Join
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apex-seo-work · 2 months
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Generative AI | High-Quality Human Expert Labeling | Apex Data Sciences
Apex Data Sciences combines cutting-edge generative AI with RLHF for superior data labeling solutions. Get high-quality labeled data for your AI projects.
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globosetechnology · 2 years
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Gts.ai is the leading annotation company, providing the highest quality training data for companies working in the artificial intelligence space.
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apcseo · 2 months
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Meta and Microsoft Unveil Llama 2: An Open-Source, Versatile AI Language Model
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In a groundbreaking collaboration, Meta and Microsoft have unleashed Llama 2, a powerful large language AI model designed to revolutionise the AI landscape. This sophisticated language model is available for public use, free of charge, and boasts exceptional versatility. In a strategic move to enhance accessibility and foster innovation, Meta has shared the code for Llama 2, allowing researchers to explore novel approaches for refining large language models.
Llama 2 is no ordinary AI model. Its unparalleled versatility allows it to cater to diverse use cases, making it an ideal tool for established businesses, startups, lone operators, and researchers alike. Unlike fine-tuned models that are engineered for specific tasks, Llama 2’s adaptability enables developers to explore its vast potential in various applications.
Microsoft, as a key partner in this venture, will integrate Llama 2 into its cloud computing platform, Azure, and its renowned operating system, Windows. This strategic collaboration is a testament to Microsoft’s commitment to supporting open and frontier models, as well as their dedication to advancing AI technology. Notably, Llama 2 will also be available on other platforms, such as AWS and Hugging Face, providing developers with the freedom to choose the environment that suits their needs best.
During the Microsoft Inspire event, the company announced plans to embed Llama 2’s AI tools into its 360 platform, further streamlining the integration process for developers. This move is set to open new possibilities for innovative AI solutions and elevate user experiences across various industries.
Meta’s collaboration with Qualcomm promises an exciting future for Llama 2. The companies are working together to bring Llama 2 to laptops, phones, and headsets, with plans for implementation starting next year. This expansion into new devices demonstrates Meta’s dedication to making Llama 2’s capabilities more accessible to users on-the-go.
Llama 2’s prowess is partly attributed to its extensive pretraining on publicly available online data sources, including Llama-2-chat. Leveraging publicly available instruction datasets and over 1 million human annotations, Meta has honed Llama 2’s understanding and responsiveness to human language.
In a Facebook post, Mark Zuckerberg, the visionary behind Meta, highlighted the significance of open-source technology. He firmly believes that an open ecosystem fosters innovation by empowering a broader community of developers to build with new technology. With the release of Llama 2’s code, Meta is exemplifying this belief, creating opportunities for collective progress and inspiring the AI community.
The launch of Llama 2 marks a pivotal moment in the AI race, as Meta and Microsoft collaborate to offer a highly versatile and accessible AI language model. With its open-source approach and availability on multiple platforms, Llama 2 invites developers and researchers to explore its vast potential across various applications. As the ecosystem expands, driven by Meta’s vision for openness and collaboration, we can look forward to witnessing groundbreaking AI solutions that will shape the future of technology.
This post was originally published on: Apppl Combine
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outsourcebigdata · 7 months
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Best data extraction services in USA
In today's fiercely competitive business landscape, the strategic selection of a web data extraction services provider becomes crucial. Outsource Bigdata stands out by offering access to high-quality data through a meticulously crafted automated, AI-augmented process designed to extract valuable insights from websites. Our team ensures data precision and reliability, facilitating decision-making processes.
For more details, visit: https://outsourcebigdata.com/data-automation/web-scraping-services/web-data-extraction-services/.
About AIMLEAP
Outsource Bigdata is a division of Aimleap. AIMLEAP is an ISO 9001:2015 and ISO/IEC 27001:2013 certified global technology consulting and service provider offering AI-augmented Data Solutions, Data Engineering, Automation, IT Services, and Digital Marketing Services. AIMLEAP has been recognized as a ‘Great Place to Work®’.
With a special focus on AI and automation, we built quite a few AI & ML solutions, AI-driven web scraping solutions, AI-data Labeling, AI-Data-Hub, and Self-serving BI solutions. We started in 2012 and successfully delivered IT & digital transformation projects, automation-driven data solutions, on-demand data, and digital marketing for more than 750 fast-growing companies in the USA, Europe, New Zealand, Australia, Canada; and more. 
-An ISO 9001:2015 and ISO/IEC 27001:2013 certified  -Served 750+ customers  -11+ Years of industry experience  -98% client retention  -Great Place to Work® certified  -Global delivery centers in the USA, Canada, India & Australia 
Our Data Solutions
APISCRAPY: AI driven web scraping & workflow automation platform APISCRAPY is an AI driven web scraping and automation platform that converts any web data into ready-to-use data. The platform is capable to extract data from websites, process data, automate workflows, classify data and integrate ready to consume data into database or deliver data in any desired format. 
AI-Labeler: AI augmented annotation & labeling solution AI-Labeler is an AI augmented data annotation platform that combines the power of artificial intelligence with in-person involvement to label, annotate and classify data, and allowing faster development of robust and accurate models.
AI-Data-Hub: On-demand data for building AI products & services On-demand AI data hub for curated data, pre-annotated data, pre-classified data, and allowing enterprises to obtain easily and efficiently, and exploit high-quality data for training and developing AI models.
PRICESCRAPY: AI enabled real-time pricing solution An AI and automation driven price solution that provides real time price monitoring, pricing analytics, and dynamic pricing for companies across the world. 
APIKART: AI driven data API solution hub  APIKART is a data API hub that allows businesses and developers to access and integrate large volume of data from various sources through APIs. It is a data solution hub for accessing data through APIs, allowing companies to leverage data, and integrate APIs into their systems and applications. 
Locations: USA: 1-30235 14656  Canada: +1 4378 370 063  India: +91 810 527 1615  Australia: +61 402 576 615 Email: [email protected]
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tagxdata22 · 2 years
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MLOps and ML Data pipeline: Key Takeaways
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If you have ever worked with a Machine Learning (ML) model in a production environment, you might have heard of MLOps. The term explains the concept of optimizing the ML lifecycle by bridging the gap between design, model development, and operation processes.
As more teams attempt to create AI solutions for actual use cases, MLOps is now more than just a theoretical idea; it is a hotly debated area of machine learning that is becoming increasingly important. If done correctly, it speeds up the development and deployment of ML solutions for teams all over the world.
MLOps is frequently referred to as DevOps for Machine Learning while reading about the word. Because of this, going back to its roots and drawing comparisons between it and DevOps is the best way to comprehend the MLOps concept.
MLOps vs DevOps
DevOps is an iterative approach to shipping software applications into production. MLOps borrows the same principles to take machine learning models to production. Either Devops or MLOps, the eventual objective is higher quality and control of software applications/ML models.
What is MLOps?
Machine Learning Operations is referred to as MLOps. Therefore, the function of MLOps is to act as a communication link between the operations team overseeing the project and the data scientists who deal with machine learning data.
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The key MLOps principles are:
Versioning – keeping track of the versions of data, ML model, code around it, etc.;
Testing – testing and validating an ML model to check whether it is working in the development environment;
Automation – trying to automate as many ML lifecycle processes as possible;
Reproducibility – we want to get identical results given the same input;
Deployment – deploying the model into production;
Monitoring – checking the model’s performance on real-world data.
What are the benefits of MLOps?
The primary benefits of MLOps are efficiency, scalability, and risk reduction. 
Efficiency: MLOps allows data teams to achieve faster model development, deliver higher quality ML models, and faster deployment and production. 
Scalability: Thousands of models may be supervised, controlled, managed, and monitored for continuous integration, continuous delivery, and continuous deployment thanks to MLOps’ extensive scalability and management capabilities. MLOps, in particular, makes ML pipelines reproducible, enables closer coordination between data teams, lessens friction between DevOps and IT, and speeds up release velocity.
Risk reduction: Machine learning models often need regulatory scrutiny and drift-check, and MLOps enables greater transparency and faster response to such requests and ensures greater compliance with an organization’s or industry’s policies.
Data pipeline for ML operations
One significant difference between DevOps and MLOps is that ML services require data–and lots of it. In order to be suitable for ML model training, most data has to be cleaned, verified, and tagged. Much of this can be done in a stepwise fashion, as a data pipeline, where unclean data enters the pipeline, and then the training, validating, and testing data exits the pipeline.
The data pipeline of a project involves several key steps:
Data collection: 
Whether you source your data in-house, open-source, or from a third-party data provider, it’s important to set up a process where you can continuously collect data, as needed. You’ll not only need a lot of data at the start of the ML development lifecycle but also for retraining purposes at the end. Having a consistent, reliable source for new data is paramount to success.
Data cleansing: 
This involves removing any unwanted or irrelevant data or cleaning up messy data. In some cases, it may be as simple as converting data into the format you need, such as a CSV file. Some steps of this may be automatable.
Data annotation: 
Labeling your data is one of the most time-consuming, difficult, but crucial, phases of the ML lifecycle. Companies that try to take this step internally frequently struggle with resources and take too long. Other approaches give a wider range of annotators the chance to participate, such as hiring freelancers or crowdsourcing. Many businesses decide to collaborate with external data providers, who can give access to vast annotator communities, platforms, and tools for any annotating need. Depending on your use case and your need for quality, some steps in the annotation process may potentially be automated.
After the data has been cleaned, validated, and tagged, you can begin training the ML model to categorize, predict, or infer whatever it is that you want the model to do. Training, validation, and hold-out testing datasets are created out of the tagged data. The model architecture and hyperparameters are optimized many times using the training and validation data. Once that is finished, you test the algorithm on the hold-out test data one last time to check if it performs enough on the fresh data you need to release.
Setting up a continuous data pipeline is an important step in MLOps implementation. It’s helpful to think of it as a loop, because you’ll often realize you need additional data later in the build process, and you don’t want to have to start from scratch to find it and prepare it.
Conclusion
MLOps help ensure that deployed models are well maintained, performing as expected, and not having any adverse effects on the business. This role is crucial in protecting the business from risks due to models that drift over time, or that are deployed but unmaintained or unmonitored.
TagX is involved in delivering Data for each step of ML operations. At TagX, we provide high-quality annotated training data to power the world’s most innovative machine learning and business solutions. We can help your organization with data collection, Data cleaning,  data annotation, and synthetic data to train your Machine learning models.
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dayslikecrazypaving · 2 years
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Fic: Technicolour (part 1/3)
5 times Narvin saw the world differently through Leela and one time she saw him.
Set between Series 2 and 6. Title taken from the song Technicolor by Sainte
Rated T: Angst,hurt and comfort
First: Sentries
Surveying the audience of assembled agents, dignitaries and guards waiting to hear Leela speak, he hadn’t ever suspected that the timelines would lead them to this moment. When he’d first met Leela he’d never ever thought he’d come to need her company. He couldn’t fathom what value she could possibly have added to any situation let alone his line of work. Gallifreyan spycraft required almost catatonic levels of stillness and observation over the median span of a human lifetime. That view shamed him now.
Before Romana’s Presidency, their contact had been limited to intelligence reports - a necessary precaution of the allowance of an alien in the heart of the citadel. Through these briefings he’d become aware of her frenetic energy, her brash attitude and forthright nature but he’d overlooked her powers of observation and whip smart stratagem. The battle against Pandora had forced them together - unlikely allies in an even more improbable conflict. In a few short weeks Leela had risen in his esteem from savage outsider to trusted confidante.
Running reconnaissance and resupply missions together, Leela had taken the lead, saving him more than once. They also took turns on watch duty in what Leela had termed the “crows nest”, but was actually the highest citadel balcony they had access to. The night was spent charting any movement they could, logging movement and trying to stop anyone raiding their much reduced supplies. The best thing about nine hours on a bare balcony hundreds of feet above the ground, exposed to the elements (and there were vanishingly few good things about those nights) was Leela’s companionship. Sometimes, they'd sit in comfortable silence, other times he’d describe the vista of the capitol and the hidden CIA passageways beneath, in case she needed them, and in return, she’d describe the edges of the outlands they could see, in case a retreat was necessary.
One night Leela had become pensive, scanning the vista with acute attention. She shifted her weight from side to side to keep her muscles from seizing up in the cold night air, but Narvin could tell that her movement was also due to unease. He waited, knowing that if Leela wished to share her thoughts, she would. He watched as she made up her mind.
“Can you teach me to draw the maps we have made on these evenings? I see them in my mind and my memory, but I want to create something we can share with those we fight alongside.” She asked, not meeting his gaze. Her body language conveyed that it was not comfortable for her to ask for his help. He agreed, very quickly, before she could change her mind about spending more time in his company than Romana had asked her to.
The next week was spent teaching her the basics of cartography, and Leela proved herself a quick study. The week after was spent with him keeping watch whilst Leela diligently annotated each data point on the map, updating with last known movements of Pandora's troops and the natural or citadel resources across the Gallifreyan vista. The map proved to be invaluable as they were forced into the ruined Academy. Much to his regret he never spoke to her directly about his appreciation for her work, letting Romana lead the praise. He didn't think his comment would be as welcomed as his President’s, especially not in Leela’s estimations.
After the Artron Forum bomb took her sight, he’d taken a risk and insisted she present that map to the guards who remained loyal. He needed to bolster her confidence and he knew that blind or not - she now knew the capitol better now than the timelords that had inhabited it for centuries. He had gathered his remaining loyal agents as well as all the guards not on duty for an evening briefing to be led by Leela. Romana watched on from the doorway as he introduced Leela. Using his most clipped tones, the voice he usually reserved for the most idiotic of newly recruited agents, he silenced the room. The majority of those present had been whispering in unbecoming, gossipy undertones. His harshness was bolstered by an approvingly stern glare from President Romana to his right. Gently, he touched Leela’s elbow to let her know she could step forward to the makeshift podium they had created in the temporary forum.
“ Lady Leela of the Sevateem, Presidential Bodyguard and Academy Tutor, will be briefing you this evening on her comprehensive cartographic project encompassing all known thoroughfares of the citadel, both above and below ground. This information might well save your lives in the coming weeks, I expect all in attendance to show Lady Leela the same deference and respect you would show to me as Coordinator.”
He sat, giving her the stage, and listened as Leela commanded the attention of the room impeccably. Unfalteringly, she taught everyone present more effectively than even the most seasoned of Academy Professors. Despite not being able to see her audience, she engaged the room completely, her passion and protective love for her adopted home shining through. What surprised him, though, was his depth of feeling for her. He wanted to live up to the esteem she held Gallifrey in. He hid these thoughts behind his omnipresent scowl at the attendees, hoping that those listening couldn’t see, especially his President.
Second - Sonata
They’d lost another member of the guard today. He’d been vaporised. His death had been brutally efficient, erasing him out of their lives in an instant. It never got easier, dealing with the immediate absence of someone you’d assumed you’d be around for centuries. Timelords' fear of their own mortality had been mollified by the gift of regenerations, but the civil war had snatched that option from too many of those he fought shoulder to shoulder with. Narvin had known of Adrianus for decades, but couldn’t have claimed friendship or kinship with the man, but he acknowledged the bravery with which he had defended Gallifrey to his last. During a time of civil war, traditional funerals were not possible, but there was a wall of remembrance in the catacombs, which could be attended by those grieving.
He had travelled down into the passageways to pay his respects when he heard a melody almost forgotten from the mists of his childhood. Someone was singing a Gallifreyan hymn of mourning. A single soprano voice echoed across the stone lined walls, arresting his journey. He could see a figure in a plain shift dress, kneeling before the wall, head bowed as she sang. Candles had been placed in front of the memorial and as his eyes focused in the darkness, Narvin consciously slowed his approach, trying to make his steps as soft and quiet as a churchmouse so as to not disturb the vocalist. It was Leela. Her voice enunciated the old high Gallifreyan song perfectly. He has not heard this melody since he was a boy at the academy. He felt his heart’s squeeze painfully in a way he tried not to identify.
Always watchful, Narvin had observed that Leela had taken the news of his death harder than most. She was not unused to loss, especially on the battlefield, but Adrianus had been Leela’s last connection to her husband, to the Andred she’d known and loved. She’d met Adrianus shortly after her arrival on Gallifrey. Serving under Andred’s command, Adrianus stood out within the guard. He was a freer spirit than most and he’d embraced Leela, despite her differences. As CIA coordinator, Narvin had tracked Leela’s friendships and filed away that info in case an interrogation was needed.
Leela finished the hymn and her final notes reverberated into the gloom of the tunnels. She bent lower and wrote something on parchment placed in front of the candles. Narvin decided he’d been a silent voyeur long enough. He deliberately flat footed his steps to make his presence known. Leela rose to her feet unperturbed by his presence as she’d recognised the cadence of his gait on approach.
Narvin decided to be brave.
“That was beautiful” he told her, as honestly as a spymaster could.
As always braver than him, Leela reached for and took his hand, briefly.
“I needed to say goodbye in a way he’d know how to hear” she replied simply. Her eyes glimmered in the candlelight full to the brim of unshod tears.
Narvin glanced down, and saw the parchment - with Andrianus’s name immaculately written in old high Gallifreyan script. That unnamed feeling traitorously knocked itself loose in his chest again and he swallowed heavily. Standing closer to her than was necessary, he held vigil with her, together in the night.
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What are the 10 best Android apps for data analysis?
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The capacity to analyze data and derive actionable insights is essential for professionals, companies, and individuals alike in today's data-driven environment. Android apps have developed into strong data analysis tools as a result of the development of mobile technology, enabling users to access, examine, and visualize data from any location. The top ten Android apps for data analysis are presented here, giving users the ability to see patterns, obtain insightful information, and make wise choices.
1. Microsoft Power BI
A well-known business intelligence product with an Android app is Microsoft Power BI. With Power BI, users can build interactive dashboards and reports, connect to a range of data sources, and share insights with peers. Users can access their Power BI through the mobile app to visually analyze data and remain current on important metrics and trends.
2. Google Analytics
Android users can track real-time website and app metrics using Google Analytics' mobile app. With the app, customers can monitor important analytics data including user activity, traffic sources, and conversion rates in addition to tracking the effectiveness of marketing campaigns. The app's tailored reports and easy-to-use UI let users keep tabs on their online presence.
3. Tableau Mobile
Tableau Mobile is an Android app that works in tandem with Tableau Desktop and Tableau Server to enable users to access and engage with Tableau visualizations. With Tableau Mobile, users can work in real-time collaboration with peers, filter insights, and explore data.
4. Qlik Sense
Android users can explore and interact with Qlik Sense analytics dashboards and results through a mobile app offered by Qlik Sense. With Qlik Sense, users can create customized dashboards, visually analyze data, and share insights with stakeholders. With the app's touch-optimized UI and responsive design, users can swiftly examine data and make decisions based on that data while they're on the road.
5. IBM Cognos Analytics
For Android users, IBM Cognos Analytics provides a mobile app that allows them to access and explore data insights from their environments. The app's built-in commenting and annotation tools let users work with colleagues while exploring interactive dashboards, reports, and visualizations. Because of the app's offline capability, users can still access important information when they're not online.
6. DataLab
Users of DataLab, an Android app for data analysis, can import, study, and visualize datasets from many sources. With DataLab, users can generate reports, perform statistical analysis, and design unique visualizations right on their Android smartphones. The software is appropriate for both professionals and students due to its broad feature set and user-friendly layout.
7. Plotly Dash
An Android mobile app is available for Plotly Dash, a robust data visualization platform, allowing users to explore and interact with Plotly charts and dashboards in mobile app development company in bangalore. With Plotly Dash, users may explore dynamic visuals, explore data, and learn from intricate datasets.
8. Data Analysis Toolpak
A number of statistical functions and data analysis tools are included in the data analysis program Data Analysis Toolpak. Regression analysis, hypothesis testing, and descriptive statistics can all be done immediately on Android smartphones with Data Analysis Toolpak. The software is a priceless tool for data analysts and researchers due to its extensive feature set and user-friendly layout.
9. Matplotlib Viewer
With the help of the Android software Matplotlib Viewer, users may access and manipulate Matplotlib visualizations on their mobile devices. With Matplotlib Viewer, users may examine intricate plots, scatterplots, and histograms to learn more about their data. For data scientists and Python fans, the app is a must-have because of its user-friendly interface and powerful rendering engine.
10. Trello
Trello is a well-known project management tool for Android that offers robust capabilities for managing, monitoring, and assessing data-driven projects in mobile app development companies in India. With Trello, users can manage tasks, work together with colleagues, and monitor progress in real time by creating boards, lists, and cards. The application's adaptable layout and customizable workflows make it a priceless resource for businesses trying to improve results and expedite data analysis processes.
Read Also: cost to develop app like Myntra
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mohalicareerpoint12 · 1 month
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Master Selenium Automation Testing at Mohali Career Point (MCP)
MCP is your gateway to mastering Selenium, the leading web-based open-source automation testing framework. With our extensive industry experience in implementing automation projects, we offer the best Selenium training in Mohali, designed to take you from the basics to advanced concepts in a real-time environment.
Why Choose Selenium?
Selenium is a preferred tool for automated testing due to its cost-effectiveness, flexibility, and support for multiple programming languages like Java, Python, Ruby, and more. It works seamlessly across all major browsers and operating systems, making it the top choice for companies worldwide.
About MCP Selenium Training
At MCP, we provide a structured learning path that includes both theoretical knowledge and practical exposure. Our expert trainers, who have hands-on experience with various automation projects, frameworks like Data Driven and Page Object Model, and tools like Appium, will guide you through each step.
What Will You Learn?
Our Selenium course is divided into six modules, each designed to cover critical aspects of Selenium and automation testing:
Module 1: Selenium Introduction
Overview of Selenium and its comparison with QTP.
Understanding Selenium components.
Introduction to Java in Selenium.
Module 2: Selenium IDE and RC
Installation and features of Selenium IDE.
Developing and running test cases in IDE.
Introduction to Selenium RC and usage of various locators.
Module 3: Core Java and OOPs Concepts
Setting up Java environment.
In-depth Java programming concepts including classes, objects, inheritance, interfaces, and exception handling.
Module 4: Selenium WebDriver and Selenium Grid
Configuration of WebDriver with Eclipse.
Cross-browser testing on Firefox, IE, Chrome.
Handling WebElements, calendar, Iframes, mouse movements, and keyboard events.
Module 5: TestNG and Testing Frameworks
Setting up TestNG with Eclipse.
Working with TestNG annotations, data providers, and creating test suites.
Developing Data-Driven and Keyword-Driven frameworks.
Module 6: Database Testing with JDBC
Installation of MySQL Database.
JDBC drivers, Connection, and ResultSet interfaces.
Performing database operations (Select, Insert, Update, Delete) using JDBC in TestNG framework.
Why MCP?
Expert Trainers: Learn from professionals with real-world experience in Selenium and automation testing.
Comprehensive Curriculum: From basic to advanced concepts, our syllabus covers everything you need to excel in Selenium.
Hands-On Projects: Gain practical experience through live project training, making you industry-ready.
Affordable Fees: Get top-notch Selenium training at competitive rates.
Flexible Learning: Choose from regular, weekend, and fast-track batches, available in both online and offline modes.
Enroll Today!
Join MCP, the leading Selenium training institute in Mohali, and kickstart your career in automation testing. Our structured course, expert guidance, and hands-on approach will prepare you for high-paying jobs in the IT industry.
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globalgrowthinsights · 2 months
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Blockchain Technology in Healthcare Market: Dissecting the Factors Steering Growth and Potential Risks
Blockchain Technology in Healthcare Market provides in-depth analysis of the market state of Blockchain Technology in Healthcare manufacturers, including best facts and figures, overview, definition, SWOT analysis, expert opinions, and the most current global developments. The research also calculates market size, price, revenue, cost structure, gross margin, sales, and market share, as well as forecasts and growth rates. The report assists in determining the revenue earned by the selling of this report and technology across different application areas.
Geographically, this report is segmented into several key regions, with sales, revenue, market share and growth Rate of Blockchain Technology in Healthcare in these regions till the forecast period
North America
Middle East and Africa
Asia-Pacific
South America
Europe
Key Attentions of Blockchain Technology in Healthcare Market Report:
The report offers a comprehensive and broad perspective on the global Blockchain Technology in Healthcare Market.
The market statistics represented in different Blockchain Technology in Healthcare segments offers complete industry picture.
Market growth drivers, challenges affecting the development of Blockchain Technology in Healthcare are analyzed in detail.
The report will help in the analysis of major competitive market scenario, market dynamics of Blockchain Technology in Healthcare.
Major stakeholders, key companies Blockchain Technology in Healthcare, investment feasibility and new market entrants study is offered.
Development scope of Blockchain Technology in Healthcare in each market segment is covered in this report. The macro and micro-economic factors affecting the Blockchain Technology in Healthcare Market
Advancement is elaborated in this report. The upstream and downstream components of Blockchain Technology in Healthcare and a comprehensive value chain are explained.
Browse More Details On This Report at @https://www.globalgrowthinsights.com/market-reports/blockchain-technology-in-healthcare-market-100580
 Global Growth Insights
Web: https://www.globalgrowthinsights.com
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veenaahuja · 2 months
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Annotate Like A Pro: Best Practices For Effective Annotation Services
Effective annotation is essential for unlocking the full potential of data-driven technologies. This blog delves into the key strategies for annotating like a pro, covering everything from data annotation best practices to annotation project management. Outsourcing annotation services to companies like EnFuse Solutions offers cost-effectiveness, scalability, access to expertise, and faster turnaround times.
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speedlauncher · 3 months
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Where i Can Download Speed Launcher
Checking out the best Video game Shelter: A Journey Simply by channel associated with Speed Launcher
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globosetechnology · 2 years
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GTS Data Collection Service is the future of data collection. We provide a reliable, efficient and cost-effective solution for collecting data from any source.
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apiscrapy · 3 months
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APISCRAPY Real Estate API – The Powerhouse Of Data Extraction
Best Real Estate API for 2024: Unlock the best real estate API for 2024 with APISCRAPY's Real Estate API. Gain seamless access to comprehensive property listings, pricing information, and market trends. Explore more at https://apiscrapy.com/real-estate-api/ About AIMLEAP – Apiscrapy
Apiscrapy is a division of Aimleap. Aimleap is an ISO 9001:2015 and ISO/IEC 27001:2013 certified global technology consulting and service provider offering AI-augmented Data Solutions, Data Engineering, Automation, IT Services, and Digital Marketing Services. AIMLEAP has been recognized as a ‘Great Place to Work®’.
With a special focus on AI and automation, we built quite a few AI & ML solutions, AI-driven web scraping solutions, AI-data Labeling, AI-Data-Hub, and Self-serving BI solutions. We started in 2012 and successfully delivered IT & digital transformation projects, automation-driven data solutions, on-demand data, and digital marketing for more than 750 fast-growing companies in the USA, Europe, New Zealand, Australia, Canada; and more. 
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Great Place to Work® certified 
Global delivery centers in the USA, Canada, India & Australia 
Our Data Solutions
APISCRAPY: AI-driven web scraping & workflow automation platform
APYSCRAPY is an AI-driven web scraping and automation platform that converts any web data into ready-to-use data. The platform is capable to extract data from websites, processing data, automate workflows, classify data and integrate ready-to-consume data into database or deliver data in any desired format. 
AI-Labeler: AI augmented annotation & labeling solution
AI-Labeler is an AI augmented data annotation platform that combines the power of artificial intelligence with in-person involvement to label, annotate and classify data, and allowing faster development of robust and accurate models.
AI-Data-Hub: On-demand data for building AI products & services
On-demand AI data hub for curated data, pre-annotated data, pre-classified data, and allowing enterprises to obtain easily and efficiently, and exploit high-quality data for training and developing AI models.
PRICESCRAPY: AI enabled real-time pricing solution
An AI and automation driven price solution that provides real time price monitoring, pricing analytics, and dynamic pricing for companies across the world. 
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outsourcebigdata · 1 month
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Best web scraping tools to look in 2024
For the most efficient web scraping, Outsource BigData is the top choice. With expert knowledge and access to the best web scraping tools, they excel in accurate and rapid data extraction from websites. Whether you need market insights, competitor analysis, or research data, Outsource BigData delivers reliable results. Streamline your data acquisition and unlock the full potential of web scraping with our advanced tools.
Visit: https://outsourcebigdata.com/how-to-select-the-best-web-scraper-tool/
About AIMLEAP
Outsource Bigdata is a division of Aimleap. AIMLEAP is an ISO 9001:2015 and ISO/IEC 27001:2013 certified global technology consulting and service provider offering AI-augmented Data Solutions, Data Engineering, Automation, IT Services, and Digital Marketing Services. AIMLEAP has been recognized as a ‘Great Place to Work®’.
With a special focus on AI and automation, we built quite a few AI & ML solutions, AI-driven web scraping solutions, AI-data Labeling, AI-Data-Hub, and Self-serving BI solutions. We started in 2012 and successfully delivered IT & digital transformation projects, automation-driven data solutions, on-demand data, and digital marketing for more than 750 fast-growing companies in the USA, Europe, New Zealand, Australia, Canada; and more. 
-An ISO 9001:2015 and ISO/IEC 27001:2013 certified  -Served 750+ customers  -11+ Years of industry experience  -98% client retention  -Great Place to Work® certified  -Global delivery centers in the USA, Canada, India & Australia 
Our Data Solutions
APISCRAPY: AI driven web scraping & workflow automation platform APISCRAPY is an AI driven web scraping and automation platform that converts any web data into ready-to-use data. The platform is capable to extract data from websites, process data, automate workflows, classify data and integrate ready to consume data into database or deliver data in any desired format. 
AI-Labeler: AI augmented annotation & labeling solution AI-Labeler is an AI augmented data annotation platform that combines the power of artificial intelligence with in-person involvement to label, annotate and classify data, and allowing faster development of robust and accurate models.
AI-Data-Hub: On-demand data for building AI products & services On-demand AI data hub for curated data, pre-annotated data, pre-classified data, and allowing enterprises to obtain easily and efficiently, and exploit high-quality data for training and developing AI models.
PRICESCRAPY: AI enabled real-time pricing solution An AI and automation driven price solution that provides real time price monitoring, pricing analytics, and dynamic pricing for companies across the world. 
APIKART: AI driven data API solution hub  APIKART is a data API hub that allows businesses and developers to access and integrate large volume of data from various sources through APIs. It is a data solution hub for accessing data through APIs, allowing companies to leverage data, and integrate APIs into their systems and applications. 
Locations: USA: 1-30235 14656  Canada: +1 4378 370 063  India: +91 810 527 1615  Australia: +61 402 576 615 Email: [email protected]
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govindhtech · 3 months
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Deloitte AI Insights: Innovations and Applications
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AI conjecture and concern have plagued the past decade.  AI’s rapid growth raises job, privacy, and ethics concerns. However, a prominent Deloitte AI leader recently attended a gathering and made excellent arguments to address one of the primary AI worries.
Deloitte AI Governance
AI Automation Job Replacement Concerns
One of the biggest concerns is job losses from automation and AI. Many workers worry that AI systems will replace human jobs, bringing mass unemployment and economic instability. Automation is already changing customer service, manufacturing, and transportation, justifying this concern.
AI as a Human Labor Supplement
The Deloitte AI leader thinks that AI can transform work and create new jobs.  AI should supplement human labor, not replace it. The CEO underlined that  AI can undertake monotonous tasks, allowing up humans to focus on more complex, inventive, and lucrative tasks.
AI can diagnose and manage large datasets in healthcare, freeing up doctors and nurses to focus on patient care and treatment planning. AI can handle tedious duties and data processing, allowing financial advisors to give clients more personalized and strategic advice.
Deloitte AI Jobs
The Development of New Employment Categories
Furthermore, the Deloitte AI executive emphasized that new job categories that were not previously present are anticipated as a result of the integration of  AI into numerous industries. These include such as data annotators, ethics experts, and  AI trainers. The need for qualified individuals with the ability to design, execute, and manage AI systems will grow as more businesses use these technologies.
AI-driven innovation will also probably lead to the emergence of whole new markets and services, which will create jobs in previously unthinkable sectors. The CEO cited earlier instances of technology breakthroughs that produced a wide range of new sectors and job prospects, such as the introduction of the internet.
Ethics and AI: A Perspective
The ethical ramifications of AI are a significant additional worry. Many people have talked about topics like privacy infringement, bias in  AI systems, and opaque decision-making processes in  AI. The AI executive from Deloitte addressed these worries by highlighting the significance of ethical AI research and legal frameworks.
Applying Moral AI Principles
In order to guarantee that AI systems are just, open, and accountable, the CEO said that Deloitte is dedicated to ethical AI practices and is actively working on creating standards and rules. This entails protecting data privacy, doing thorough testing for biases, and keeping an open mind on AI operations.
To further encourage the creation of moral AI frameworks, Deloitte also works with a range of stakeholders, such as governmental agencies, academic institutions, and business partners. The objective of these partnerships is to develop a well-rounded strategy that optimizes  AI’s advantages while minimizing its hazards.
The Function of Consultants in  AI Ethics
Consultants in AI ethics are playing a more and bigger role. These experts are responsible for evaluating AI systems for moral compliance and offering organizations guidance on responsible AI deployment best practices. According to the Deloitte AI executive, more companies will understand the necessity of ethical oversight in their AI initiatives, increasing demand for these positions.
Deloitte AI Services
AI’s Security and Privacy Effects
AI privacy and security are vital. AI systems’ ability to handle massive amounts of personal data raises privacy and data breach concerns. The Deloitte AI leader assures them that fixing these vulnerabilities is a top priority.
Data Privacy Rules
Deloitte invests heavily on data privacy to protect user data. To comply with global data protection standards like the GDPR, use robust encryption, create defined data governance principles, and monitor their application.
The CEO also emphasized the value of openness and user permission. Users ought to have the choice to refuse data gathering and be told about how their data is being used. Companies may reduce the risks connected with  AI and foster customer trust by upholding strict standards of data protection.
Maintaining  AI Security
Deloitte’s security efforts are concentrated on creating AI systems that can withstand intrusions. This include using cutting-edge cybersecurity tactics, conducting routine security assessments, and keeping up with new threats. Deloitte wants to stop bad actors from abusing AI systems and doing damage, which is why they priorities security.
AI’s Role in Society Future
In closing, the AI executive from Deloitte provided an upbeat outlook for the application of AI in society. The CEO underlined AI’s revolutionary potential to enhance lives, spur economic growth, and resolve challenging global issues while noting its difficulties and concerns.
 AI in Medical Field
AI has great potential in healthcare.  AI is being developed to improve patient outcomes, therapy personalization, and disease identification. AI-powered diagnostic tools can accurately evaluate medical pictures to make cancer diagnoses earlier and more accurately.
Deloitte AI Academy
AI has the power to completely transform the educational process. AI-driven systems have the ability to give students individualized learning plans, pinpoint areas in which they need to grow, and recommend resources that will best support their success. As a result, students of all ages may benefit from more efficient and interesting learning opportunities.
AI for Sustainability in the Environment
 AI is also going to be a big part of solving environmental problems.  AI can offer creative solutions to help fight climate change and advance sustainability, from monitoring and safeguarding biodiversity to optimizing energy use in smart networks. The Deloitte AI executive underlined that the company’s main area of concentration is using AI for environmental goals.
In conclusion
According to the Deloitte AI executive, AI’s future is bright. The executive eases concerns about  artificial intelligence by highlighting ethical development, privacy and security, job creation, and societal benefits. All stakeholders must work together to ensure that ethical values and human wellbeing drive AI development and use.
Read more on govindhtech.com
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