More Information
  • Utilize the power of R to handle data extraction, manipulation, and exploration techniques
  • Use R to visualize data spread across multiple dimensions and extract useful features
  • Explore the underlying mathematical and logical concepts that drive machine learning algorithms
  • Delve into the world of analytics to correctly predict situations 
  • Apply reusable code and build complete machine learning systems 
  • Harness the power of robust and optimized R packages

With powerful features and packages, R empowers users to build sophisticated machine learning systems to solve real-world data problems.

This video course takes you on a data-driven journey that starts with the very basics of R and machine learning. You will then work on three different projects to apply the concepts of machine learning. Each project will help you to understand, explore, visualize, and derive domain- and algorithm-based insights.

By the end of this course, you will have learned to apply the concepts of machine learning to data-related problems and solve them with help of R.

All the code and supporting files for this course are available on Github at

Style and Approach

The course is an enticing journey that starts from the very basics and gradually picks up the pace as it unfolds. Each topic is explained with the help of a project that solves a real-world problem hands-on, thus giving you a deep insight into the world of machine learning.

  • Learn to build your own machine learning system with this example-based practical guide
  • Get to grips with machine learning concepts through exciting real-world examples
  • Visualize and solve complex problems by using power-packed R constructs and its robust packages for machine learning
Course Length 4 hours 15 minutes
ISBN 9781789536829
Date Of Publication 30 May 2018


Dipanjan Sarkar

Dipanjan (DJ) Sarkar is a Data Scientist at Intel, leveraging data science, machine learning, and deep learning to build large-scale intelligent systems. He holds a master of technology degree with specializations in Data Science and Software Engineering. He has been an analytics practitioner for several years now, specializing in machine learning, NLP, statistical methods, and deep learning. He is passionate about education and also acts as a Data Science Mentor at various organizations like Springboard, helping people learn data science. He is also a key contributor and editor for Towards Data Science, a leading online journal on AI and Data Science. He has also authored several books on R, Python, machine learning, NLP, and deep learning.

Raghav Bali

Raghav Bali is a Data Scientist at Optum (United Health Group). His work involves research & development of enterprise level solutions based on Machine Learning, Deep Learning and Natural Language Processing for Healthcare & Insurance related use cases. In his previous role at Intel, he was involved in enabling proactive data driven IT initiatives. He has also worked in ERP and finance domains with some of the leading organizations in the world. Raghav has also authored multiple books with leading publishers. Raghav has a master’s degree (gold medalist) in Information Technology from International Institute of Information Technology, Bangalore. Raghav loves reading and is a shutterbug capturing moments when he isn’t busy solving problems.