R and Machine Learning Fundamentals
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R and Machine Learning Fundamentals

Learn all the skills you need to start using R for machine learning
0.0 (0 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
3 students enrolled
Created by Packt Publishing
Last updated 7/2017
English
Curiosity Sale
Current price: $10 Original price: $200 Discount: 95% off
30-Day Money-Back Guarantee
Includes:
  • 1.5 hours on-demand video
  • 7 Articles
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Explore the basic data types and control structures in R
  • Understand the split-apply-combine paradigm for data manipulation
  • Learn how to visualize data using ggplot2
  • Get familiar with various classes of machine learning algorithms: supervised, unsupervised, reinforcement, and deep learning
  • Understand basics of the caret package and machine learning workflows by completing a mini project
View Curriculum
Requirements
  • Specifically anyone with none or minimal prior experience with programming.
Description

R is one of the most popular languages used for machine learning and arguably, the best entry point to the fascinating world of machine learning (ML). If you're interested to explore both the programming and machine learning world with R, then go for this course.

This course is a blend of text, videos, code examples, assessments, case studies, and a mini project which together makes your learning journey all the more exciting and truly rewarding. It is meticulously designed and developed in order to empower you with all the right and relevant information on R.

Let’s take a look at this learning journey. The course starts with teaching you how to set up the R environment, which includes installing RStudio and R packages. You will learn the various data types, operators, and control structures. You will then understand the split-apply-combine paradigm. You will see how to build effective data visualization using the widely popular ggplot2 library. The course also demonstrates a case study on the very famous Iris dataset.

Moving ahead, you will be introduced to the various aspects of machine learning—supervised, unsupervised, reinforcement, and deep learning. Machine learning aims to uncover hidden patterns, unknown correlations, and find useful information from data. This course aims to make you proficient enough to write R programs to perform various ML tasks irrespective of your previous programming experience and skill level. You will go through the different types of machine learning and when it's to be used along with a case study. Finally, you will look at a full-fledged project that will teach you how to build machine learning models.

By the end of this course, you will have a good knowledge of R principles in both programming and machine learning which you can use as a springboard to further develop your expertise.

About the Author

Akash Tandon is a Data Engineer at RedCarpet (a Y-Combinator and Google Startup Launchpad startup) with his primary responsibilities including setup and maintenance of the organization’s Machine Learning infrastructure. He’s also a data science competitions enthusiast and has worked on various competitions with notable results on various platforms, including Kaggle, HackerEarth and Analytics Vidhya. An avid open source software (OSS) enthusiast, he has worked thrice with the the organization, R project of Statistical computing, under the Google Summer of Code programs, both as a student and mentor.

Who is the target audience?
  • The course is intended for both professionals and students.
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Operators
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In this video, you will learn how to write functions in R. Particularly, you will:

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Split-Apply-Combine
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Supervised and Unsupervised Learning
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Deep Learning
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Reinforcement Learning
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About the Instructor
Packt Publishing
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Packt has been committed to developer learning since 2004. A lot has changed in software since then - but Packt has remained responsive to these changes, continuing to look forward at the trends and tools defining the way we work and live. And how to put them to work.

With an extensive library of content - more than 4000 books and video courses -Packt's mission is to help developers stay relevant in a rapidly changing world. From new web frameworks and programming languages, to cutting edge data analytics, and DevOps, Packt takes software professionals in every field to what's important to them now.

From skills that will help you to develop and future proof your career to immediate solutions to every day tech challenges, Packt is a go-to resource to make you a better, smarter developer.

Packt Udemy courses continue this tradition, bringing you comprehensive yet concise video courses straight from the experts.