#introduction to machine learning ppt

[khushi1902]

First Week into Co-Op

Was excited for the fit..

And absolutely loved it with the ID and WestJet tie.

The First Day, 11 January was my training day. It was all about introduction to the GSA and GSLs and then we went for an awesome airport tour. Learned various spots at terminal 3 and till the tour lasted, I was dying to sit and relax because I had my heels and it was giving me tremendous pain. Anyway, got a break and rejuvenated and went for our spot to experience what it will be like working at kiosks, helped several passengers, and then it was time for our learning through ppts, and ended the day perfectly with lot of enthusiasm.

All set for placement day 1, I was excited and felt like a WestJetter. It was new and exciting to help passengers at kiosks. The position was changing me to be a helpful person and I absolutely loved the feeling to assist when someone struggles to get their boarding pass or bag tags at kiosks.

By the time, I learned several things and the most fun thing is directing passengers when asking about airline counters other than WestJet. I also got to know about the issue of accepting bags from connecting flights at baggage drop-off. It was because the boarding pass was from a different airline and the machines won't accept those so we would drop it at the other side. Eventually, it became my favorite part during the whole shift, as this was the time I am properly doing all the things on my own which was checking destination, ETD and flight no. to direct them to their gates.

I explained this procedure to two of my classmates in my last shift.

Overall, loving the journey of being a WestJetter, and also I learned the basics of printing boarding passes and adding baggage and baggage tags at check-in counters. I usually observe this when it is not busy at the kiosks. The process seems interesting as I had a course where we use to book flights and add the services at Amadeus and it was my favorite course.

[tuteeducation-blog]

BENEFITS OF ONLINE TUITION IN INDIA

So currently we live in the 21st century, the century which has changed the world upside down and introduced some unforgettable inventions. One of them is online Technology! It has created a huge impact in the way education is delivered today and its benefits are experienced by the entire education sector. Many of the technologies create minimal impact or fail, however, the progress in the Education sector using online technology, especially in the fields of medical science, engineering, and commerce is unstoppable. Educators and students can now actually have the liberty to say, yes this can be done in just a fraction of seconds.

Now, What exactly are the benefits of online tuition?

1. PAPERLESS ENVIRONMENT

The very first and most important impact of online tuition in India is, it is trying to create a paperless environment so that no more trees need to be brought down. Schools and colleges took the initiative of going paperless by introducing E-textbooks and E-notebooks where students just need a tab or a good laptop where he can view the contents and write the notes with the help of online tutors.  Many of the institutes also introduced special tabs for writing the exams.

2. INTERACTIVE STUDIES

The traditional method of studies was, where the teacher used to see the textbook, read the content, draw diagrams on the board and ask the students to imagine exactly what she tried to explain. Well, online tuition  helped to introduce smart-boards and projectors where the online tutor just opened the picture or played a video or a documentary related to the particular topic. So,no more mundane studies but some real-time studies with all the enthusiasm.

3. NO MORE KILLING OF ANIMALS

As you know for biology/medical students studying dissection is very much important and for this traditionally live animals were used but now with the introduction of 3D GRAPHICS they can do the exact work with machines with the help of online lessons.

4. NO NEED TO MEMORIZE

Online tuition not only made it easy to learn for students but also for teachers to teach. The benefit of online tuition technology can thus be seen where teachers no longer need to memorize but instead can make PPTs with the help of live tuition tools like powerpoint and give a summary of the topic as well as show documentary related to the particular topic if available.

5. DISTANT LEARNING

The major and most effective impact created by online tuition in India and rest of the world is distant learning. Teachers and students no need to be at the same place but can fix timings that suit their convenience and do studies through online media. This gave rise to the idea of online classes where students need not  actually visit the place but just stay online and teachers can teach from 1 to as many students at the same time.

6. LOWERS TUITION PRICES AND IS COST EFFECTIVE

You don’t need to pay extra money for your tuition instead all you can do is attend or watch the recorded sessions and learn through that. All you need is a good internet connection. Live sessions are also possible now at lower prices, also you don’t need to wait for the teacher to fix the tuition timings you can study at your own time, maybe even at midnight. You don’t even need to spend extra money for learning different types of languages and pay different fees for learning each language.

7. NEW TECHNOLOGY AND PROMOTES MODERNISATION

Traditionally it was very difficult for teachers to teach specially-abled students as well as it was also difficult for the students to understand and learn what the teacher was trying to teach them. But now with the introduction of special methods such as Voice Recognition, Text-to-Speech Converter, Translator, Volume Control, Word Prediction Software and so on it has now become easy.  In India we now also have a particular school app which looks after the attendance, emailing them about portions, exam timetables, etc. of students as well as teachers with the introduction of bio-metrics and online learning platform in India. Online tuition also promotes being modern and allows everyone to learn the basics of technology.

The major question is

How online tuitions in India and technology are evolving together?

Now as we can see technology has made it a lot easy, for students to learn and memorize their content with the help of interactive graphics and videos but this is not the only benefit of technology in education. It has also helped students to explain and share what they have learnt so far through this digital media and it has become easy for them to explain in exact terms. Technological studies gave rise to more technological developments, where the students created and invented technologies which we are using today, technology gave rise to more technological experts by putting an interest in the minds of students to dig in detail about, what more can online tuition technology do?

Similarly, technology has also led to the creation of online classes in India and TUTE EDUCATION is one such example. If you want to experience and check the fact if what I said is true and learn interactively you can click here https://www.tute.in 

[machinelearningintroduction-blog]

A Concise Prologue to Counterfeit consciousness For Typical Individuals

Of late, computerized reasoning has been especially the hotly debated issue in Silicon Valley and the more extensive tech scene. To those of us associated with that scene it feels like a staggering energy is working around the theme, with a wide range of organizations building A.I. into the center of their business. There has additionally been an ascent in A.I.- related college courses which is seeing a flood of amazingly splendid new ability moving into the work showcase. Be that as it may, this isn't a basic instance of affirmation inclination - enthusiasm for the point has been on the ascent since mid-2014. The clamor around the subject is just going to increment, and for the layman it is all exceptionally befuddling. Contingent upon what you read, it's anything but difficult to trust that we're set out toward a prophetically catastrophic Skynet-style decimation because of chilly, ascertaining supercomputers, or that we're all going to live perpetually as absolutely computerized substances in some sort of cloud-based fake world. At the end of the day, either The Eliminator or The Lattice are unavoidably going to wind up plainly irritatingly prophetic. Would it be advisable for us to be concerned or energized? What's more, what does everything mean? Will robots assume control over the world? When I hopped onto the A.I. temporary fad in late 2014, I knew almost no about it. In spite of the fact that I have been included with web advancements for more than 20 years, I hold an English Writing degree and am more connected with the business and inventive conceivable outcomes of innovation than the science behind it. I was attracted to A.I. due to its positive potential, yet when I read notices from any semblance of Stephen Peddling about the prophetically calamitous perils hiding in our future, I normally moved toward becoming as worried as any other person would. So I did what I typically do when something stresses me: I began finding out about it with the goal that I could comprehend it. Over a year of steady perusing, talking, tuning in, viewing, tinkering and contemplating has driven me to a really strong comprehension of what everything means, and I need to spend the following couple of passages sharing that learning in the expectations of edifying any other person who is interested however gullibly anxious of this astonishing new world. Gracious, in the event that you simply need the response to the feature over, the appropriate response is: yes, they will. Too bad. How the machines have figured out how to learn The principal thing I found was that counterfeit consciousness, as an industry term, has really been going since 1956, and has had numerous blasts and busts in that period. In the 1960s the A.I. industry was washing in a brilliant time of research with Western governments, colleges and huge organizations tossing huge measures of cash at the segment in the expectations of building an overcome new world. Yet, in the mid seventies, when it ended up noticeably evident that A.I. was not conveying on its guarantee, the industry bubble burst and the financing went away. In the 1980s, as PCs turned out to be more prominent, another A.I. blast developed with comparative levels of brain boggling speculation being filled different endeavors. Yet, once more, the division neglected to convey and the inescapable bust took after. To comprehend why these blasts neglected to stick, you initially need to comprehend what counterfeit consciousness really is. The short response to that (and trust me, there are long answers out there) is that A.I. is various distinctive covering innovations which comprehensively manage the test of how to utilize information to settle on a choice about something. It fuses a variety of controls and advancements (Enormous Information or Web of Things, anybody?) yet the most critical one is an idea called machine learning. Machine adapting fundamentally includes nourishing PCs a lot of information and giving them a chance to examine that information to extricate designs from which they can reach inferences. You have most likely observed this in real life with confront acknowledgment innovation, (for example, on Facebook or current computerized cameras and cell phones), where the PC can recognize and outline human faces in photos. To do this, the PCs are referencing a huge library of photographs of individuals' appearances and have figured out how to recognize the qualities of a human face from shapes and hues arrived at the midpoint of out finished a dataset of countless distinctive illustrations. This procedure is essentially the same for any utilization of machine learning, from misrepresentation location (examining buying designs from Visa buy histories) to generative craftsmanship (investigating designs in sketches and haphazardly creating pictures utilizing those educated examples). As you may envision, crunching through huge datasets to extricate designs requires a Considerable measure of PC preparing power. In the 1960s they just didn't have machines sufficiently intense to do it, which is the reason that blast fizzled. In the 1980s the PCs were sufficiently capable, however they found that machines just learn adequately when the volume of information being bolstered to them is sufficiently substantial, and they were not able source sufficiently expansive measures of information to encourage the machines. At that point came the web. Not exclusively did it take care of the figuring issue for the last time through the advancements of distributed computing - which basically enable us to access the same number of processors as we require at the touch of a catch - however individuals on the web have been creating a greater number of information consistently than has ever been delivered in the whole history of planet earth. The measure of information being delivered consistently is totally mind-boggling. What this implies for machine learning is noteworthy: we now have all that could possibly be needed information to really begin preparing our machines. Think about the quantity of photographs on Facebook and you begin to comprehend why their facial acknowledgment innovation is so exact. There is presently no significant boundary (that we at present know about) anticipating A.I. from accomplishing its potential. We are just barely beginning to work out what we can do with it. At the point when the PCs will have a problem solving attitude There is a celebrated scene from the film 2001: A Space Odyssey where Dave, the principle character, is gradually handicapping the manmade brainpower centralized server (called "Hal") after the last has broke down and chosen to attempt and slaughter every one of the people on the space station it was intended to run. Hal, the A.I., challenges Dave's activities and frightfully declares that it fears biting the dust. This motion picture represents one of the huge feelings of trepidation encompassing A.I. by and large, to be specific what will happen once the PCs begin to think for themselves as opposed to being controlled by people. The dread is legitimate: we are now working with machine learning builds called neural systems whose structures depend on the neurons in the human mind. With neural nets, the information is encouraged in and afterward prepared through an immeasurably complex system of interconnected focuses that construct associations between ideas similarly as affiliated human memory does. This implies PCs are gradually beginning to develop a library of examples, as well as ideas which eventually prompt the fundamental establishments of comprehension rather than just acknowledgment. Envision you are taking a gander at a photo of some individual's face. When you initially observe the photograph, a ton of things occur in your cerebrum: in the first place, you perceive that it is a human face. Next, you may perceive that it is male or female, youthful or old, dark or white, and so forth. You will likewise have a snappy choice from your mind about whether you perceive the face, however some of the time the acknowledgment requires further speculation relying upon how regularly you have been presented to this specific face (the experience of perceiving a man yet not knowing straight far from where). The greater part of this happens essentially in a flash, and PCs are now fit for doing the greater part of this as well, at practically a similar speed. For instance, Facebook can recognize faces, as well as reveal to you who the face has a place with, if said individual is likewise on Facebook. Google has innovation that can distinguish the race, age and different qualities of a man construct just with respect to a photograph of their face. We have made considerable progress since the 1950s. Be that as it may, genuine manmade brainpower - which is alluded to as Simulated General Insight (AGI), where the machine is as cutting edge as a human cerebrum - is far off. Machines can perceive faces, however despite everything they don't generally realize what a face is. For instance, you may take a gander at a human face and induce a considerable measure of things that are drawn from a massively confused work of various recollections, learnings and emotions. You may take a gander at a photograph of a lady and figure that she is a mother, which thusly may influence you to expect that she is magnanimous, or in reality the inverse relying upon your own particular encounters of moms and parenthood. A man may take a gander at a similar photograph and discover the lady appealing which will lead him to make constructive suppositions about her identity (affirmation predisposition once more), or on the other hand find that she takes after an insane ex which will nonsensically influence him to feel adversely towards the lady. These luxuriously fluctuated yet regularly strange considerations and encounters are what drive people to the different practices - great and awful - that portray our race. Edginess frequently prompts advancement, fear prompts animosity, et cetera. For PCs to really be risky, they require some of these enthusiastic impulses, yet this is an extremely rich, complex and multi-layered embroidered artwork of various ideas that is exceptionally hard to prepare a PC on, regardless of how best in class neural systems might be. We will arrive one day, however there is a lot of time to ensure that when PCs do accomplish AGI, we will even now have the capacity to turn them off if necessary. In the interim, the advances at present being made are discovering an ever increasing number of valuable applications in the human world. Driverless autos, moment interpretations, A.I. cell phone aides, sites that plan themselves! These headways are proposed to improve our lives, and all things considered we ought not be anxious yet rather amped up for our misleadingly clever future. Marc Squat is Chief and Organizer of Firedrop, the world's most developed web designer that utilizations counterfeit consciousness to consequently assemble your site in under 60 seconds. Discover more at https://goo.gl/qBkSzA

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RMail Gateway AI can Read Content in Emails and Now in Attachments Too

Don’t move to that cabin in the woods just yet.

“If I have to read one more article or see one more talking head on TV rant about the coming AI apocalypse, about how the Terminator/Matrix movies are coming to reality, about how my job will disappear as soon as next week, I’ll move to a cabin in the woods!” This quotation has been uttered en masse all year long, in some form or another, and most recently by Taylor Swift (kidding).

Yes, we are obviously entering an era of tremendous change and potential. Economist Paul Krugman of The New York Times recently wrote that the changes soon to be wrought by AI could surpass the disruption that we all experienced with the internet over the last 25+ years. (This, however, could be a comparatively low bar, as economic productivity studies have shown that the introduction of the simple washing machine in the mid 20th century has enabled more productivity than the internet.)

The unknown is known to drive some people up the wall in terms of dire predictions, but instead of fear mongering around AI, we’d like to present a case for how we at RPost are doing our part to steer and use AI towards real good and real productivity increases that do not mean people will be back on bread lines.

As we announced yesterday (read our recent news here) we have made RMail Gateway smarter, with new AI that can read content in emails and now, importantly, in attachments. Rather than having our AI talk back to you, we’ve decided to simply let it do its thing – it can now make decisions on which email must be sent encrypted for privacy compliance, double encrypted for secrecy, tracked for proof of delivery, or actively monitored at the recipient and beyond for cybercriminal eavesdropping --- all based on what the RMail AI reads in these messages. And just like Chat GPT, RMail AI does not retain any message content. When will these enhancements launch? They already did!

Yes, RMail Gateway AI can now read content that is in a wide variety of formats, including content in message bodies, headers, and now in attachment file formats including all forms of DOC, XLS, PPT, TXT, PDF, among others.

As you may know, we’ve been focused on building security-centric AI into our RMail products for some time now, and we’re pleased to report that you’re able to benefit from these learnings, in addition to the wave of content-reading-and-learning AI, by enabling our RMail Gateway offering. Based on what RMail Gateway AI internalizes, it can decide how best to deliver, secure, encrypt, track outbound messages. It will even—in a split second—slog through more bland insurance, legal, finance, or medical documents and make security-centric decisions automatically. Below we have a chart that hopefully simplifies the process:

(Important note: for GDPR, Swiss FINMA, and other legal considerations, customers in Europe can opt for dedicated Europe-based infrastructure that is entirely isolated from rest-of-world processing infrastructures.)

RMail Gateway and its advanced AI can be set up in minutes. RPost provides white glove customer onboarding led by RPost cybersecurity experts, for customers directly or for MSPs. RMail and RMail Gateway AI are additionally available with automated provisioning through the Ingram Micro Global Cloud in more than 20 international regions.

And here’s a fun aside: We’re looking to give our new AI a fun name—a la Bard (by Google) and GPT (by Open AI / Microsoft). Please let us know your thoughts  and if you have a name we could use. If we wind up using it, there will be a special discount for you.

Feel free to contact us to learn more about RMail Gateway and how it can lead to genuinely good things for you and your company.

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An Introduction to 3D Computer Vision Techniques and Algorithms

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Introduction to R Programming

With the development of digitalization in the modern era, many software programs have launched over the years. This software promotes automatic functioning that provides lump-sum benefits to the users and helps offer valuable results. R Programming language is one such software that was created for statistical and data mining purposes. If you want to learn more about this field, USA R Programming Assignment help can come in handy.

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[machinelearningintroduction-blog]

A Brief Prologue to the Mechanical Procedure and Mechanization

The term Mechanical Process Mechanization or basically RPA, is drawing increasingly consideration these days and has placed individuals in a predicament that whether it is more right than wrong to utilize it or not. Given here is a review of this innovation and different advantages identified with it and will help you in choosing whether it is the correct decision for business or profession, or not. Above all else you have to know, what is implied by Mechanical Process Mechanization or as essentially stated, RPA. The utilization of programming alongside machine learning and computerized reasoning to oversee high-volume redundant errands is named as Mechanical Process Mechanization. The RPA programming can conform to the fluctuating conditions, special cases and new circumstances, which makes it not quite the same as the customary IT mechanization. The utilization of this product will permit huge and also little scale associations to perform back-office and center office assignments with fast. The presentation of this innovation has changed the antiquated way we used to consider the business procedure and has likewise brought about an expansion in efficiency by quickening the assignment that prior required man power to perform. The extent of mechanical autonomy is extending and isn't recently restricted to a particular industry. Ideal from car to aviation, it is presently being utilized as a part of managing an account, shopper items, social insurance, and some more, RPA can be utilized as a part of these distinctive divisions particularly. With the utilization of this innovation, associations can bring down their working costs, diminish process durations, spare their representatives from repetitive undertakings and can improve general profitability. It helps in the utilization of unequivocal advancements that can motorize the unexceptional and institutionalized undertakings, giving more prominent yield and that too with a littler speculation. Alternate advantages of Mechanical Process Robotization, for a business are: Better control: It gives better control over various business forms and enables them to moderate dangers and assemble more benefit. Enhanced basic leadership: It gives the capacity to gather, store, arrange and examine information that permits business examination to settle on better choices. Cost sparing: With the utilization of this innovation, the aggregate operational cost should be chopped around 25-half. Improved incomes: Since the assignments get robotized and can be performed speedier, which implies brisk returns and benefits. IT bolster and administration: The usage of RPA can help in enhancing the administration work area operations and checking of system gadgets additionally turn out to be simple with this innovation. Flexibility: It is an exceptionally adaptable innovation that is material in various businesses and can embrace a wide assortment of errands. Quality and exactness: The quality and precision of the work will enhance with the presentation of Mechanical Process Computerization as there are no odds of human mistake. Robotized undertakings: As talked about prior likewise, the utilization of the RPA innovation can computerize the redundant errands and spare representatives from its fatigue. In the wake of taking a gander at all the upsides of this innovation, one might say that RPA has certainly brought imaginative answers for the organizations all around the world, working models that receive robotization, and will along these lines permit cutting of costs, driving efficiencies and enhancing quality. Trep Helix with a rich affair of 8 years in instructional outlining and web based preparing, has been additionally associated with composing innovative articles and web journals. She has composed a few articles for Multisoft Virtual Foundation, an unmistakable establishment that has been giving the hopefuls web based preparing on various expert courses. Visit: http://bit.ly/2yotiz6

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Introduction to Computer Science 

In the Information Age, digitalization has become the new survival kit. With the latest technologies and machines, everything around us has become twice as comfortable. The computer is one such tool that has made the life of man smooth flowing. The Science that helps us to study this subject carefully, is called Computer Science.  

Computer Science was first developed in 1673 when Gottfried Leibniz invented the digital mechanical computer. Gradually, the science of computer helped different scientists to form contemporary computer science that has driven man to ease their functions. USA Computer science assignment writing help can guide you to learn more about it. 

The study of processes that interact with data is called Computer Science. Microsoft Excel, Calculator, HTML and other features are some of the major apps that help complete the functions of a computer. Thus, the science that helps us to understand a computer in-depth and its functions correctly are called Computer Science.  

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Artificial Neural Networks(ANN) Made Easy ##UdemyOnlineTraining ##UdemyFreeCoupons #Artificial #Easy #NetworksANN #Neural Artificial Neural Networks(ANN) Made Easy Course Covers below topics in detail Quick recap of model building and validation Introduction to ANN Hidden Layers in ANN Back Propagation in ANN ANN model building on Python TensorFlow Introduction Building ANN models in TensorFlow Keras Introduction ANN hyper-parameters Regularization in ANN Activation functions Learning Rate and Momentum Optimization Algorithms Basics of Deep Learning Pre-requite for the course.  You need to know basics of python coding You should have working experience on python packages like Pandas, Sk-learn You need to have basic knowledge on Regression and Logistic Regression You must know model validation metrics like accuracy, confusion matrix You  must know concepts like over-fitting and under-fitting In simple terms, Our Machine Learning Made Easy course on Python is the pre-requite. Other Details Datasets, Code and PPT are available in the resources section within the first lecture video of each session. Code has been written and tested with latest and stable version of python and tensor-flow as of Sep2018 Who this course is for: Beginners in Machine Learning Beginners in TensorFlow Beginners in Deep Learning Data Science Aspirants Computer Vision students Engineering , Mathematics and science students Data Analysts and Predictive Modelers 👉 Activate Udemy Coupon 👈 Free Tutorials Udemy Review Real Discount Udemy Free Courses Udemy Coupon Udemy Francais Coupon Udemy gratuit Coursera and Edx ELearningFree Course Free Online Training Udemy Udemy Free Coupons Udemy Free Discount Coupons Udemy Online Course Udemy Online Training 100% FREE Udemy Discount Coupons https://www.couponudemy.com/blog/artificial-neural-networksann-made-easy/

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DSO 530: Applied Modern Statistical Learning Techniques

DSO 530: Applied Modern Statistical Learning Techniques

Very useful class for R lovers! :) this class is taught by Dr. 

Abbass Al Sharif

Website Link: http://ift.tt/2wSjiAF

Syllabus

Download Course Syllabus

Slides

Chapter 2: Statistical Learning- pdf (part 1, part 2), ppt (part 1, part 2)

Chapter 3: Linear Regression- pdf, ppt

Chapter 4: Classification- pdf (part 1, part 2), ppt (part 1, part 2)

Chapter 5: Resampling Methods- pdf, ppt

Chapter 6: Linear Model Selection and Regularization- pdf, ppt

Chapter 7: Moving Beyond Linearity

Chapter 8: Tree-Based Methods- pdf (part 1, part 2), ppt (part 1, part 2)

Chapter 9: Support Vector Machines- pdf, ppt

Chapter 10: Unsupervised Learning- pdf, ppt

R Code with Explanations

KNN for Classification: pdf

Simple Linear Regression: html, pdf

Multiple Linear Regression: html, pdf

Logistic Regression, LDA, QDA: pdf

(Similar documents will be added during the Fall 2014 semester)

Project

Project Description: Download

Sample 1: What Causes Retweets?

Sample 2: Purchasing Lemons at an Auction

Sample 3: Factors Driving GDP Growth

Sample 4: Finding Happiness

Sample 5: Donor Trends for a Non-Profit Organization

Sample 6: Breaking Vegas

Sample 7: Analyzing Biochemical Properties to Grade Wine Quality

Sample 8: Superball Predictions

Sample 9: How Could High School Prospects Increase their Chances at NFL Success?

Sample 10: Analysis of Determinants of Peer-to-Peer Load Default

Sample 11: SPAM Classification

Book

"An Introduction to Statistical Learning with Applications in R” by James, Witten, Hastie, and Tibshirani.

Book Webpage        Datasets        R Lab Code        ISLR R Package

R Video Casts

Introduction to R

Writing R Functions

Linear Regression in R

Logistic Regression in R

LDA, QDA, and KNN in R

Cross Validation in R

Decision Trees in R (Classification)

Decision Trees in R (Regression)

via Blogger http://ift.tt/2wYtBPQ

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