R: Unleash Machine Learning Techniques

More Information
Learn
  • Get to grips with R techniques to clean and prepare your data for analysis, and visualize your results
  • Implement R machine learning algorithms from scratch and be amazed to see the algorithms in action
  • Solve interesting real-world problems using machine learning and R as the journey unfolds
  • Write reusable code and build complete machine learning systems from the ground up
  • Learn specialized machine learning techniques for text mining, social network data, big data, and more
  • Discover the different types of machine learning models and learn which is best to meet your data needs and solve your analysis problems
  • Evaluate and improve the performance of machine learning models
  • Learn specialized machine learning techniques for text mining, social network data, big data, and more
About

R is the established language of data analysts and statisticians around the world. And you shouldn’t be afraid to use it…

This Learning Path will take you through the fundamentals of R and demonstrate how to use the language to solve a diverse range of challenges through machine learning. Accessible yet comprehensive, it provides you with everything you need to become more a more fluent data professional, and more confident with R.

In the first module you’ll get to grips with the fundamentals of R. This means you’ll be taking a look at some of the details of how the language works, before seeing how to put your knowledge into practice to build some simple machine learning projects that could prove useful for a range of real world problems.

For the following two modules we’ll begin to investigate machine learning algorithms in more detail. To build upon the basics, you’ll get to work on three different projects that will test your skills. Covering some of the most important algorithms and featuring some of the most popular R packages, they’re all focused on solving real problems in different areas, ranging from finance to social media.

This Learning Path has been curated from three Packt products:

Features
  • Build your confidence with R and find out how to solve a huge range of data-related problems
  • Get to grips with some of the most important machine learning techniques being used by data scientists and analysts across industries today
  • Don’t just learn – apply your knowledge by following featured practical projects covering everything from financial modeling to social media analysis
Page Count 1123
Course Length 33 hours 41 minutes
ISBN 9781787127340
Date Of Publication 23 Oct 2016

Authors

Brett Lantz

Brett Lantz (@DataSpelunking) has spent more than 10 years using innovative data methods to understand human behavior. A sociologist by training, Brett was first captivated by machine learning during research on a large database of teenagers' social network profiles. Brett is a DataCamp instructor and a frequent speaker at machine learning conferences and workshops around the world. He is known to geek out about data science applications for sports, autonomous vehicles, foreign language learning, and fashion, among many other subjects, and hopes to one day blog about these subjects at Data Spelunking, a website dedicated to sharing knowledge about the search for insight in data.

Cory Lesmeister

Cory Lesmeister has over 14 years of quantitative experience and is currently a senior data scientist for the advanced analytics team at Cummins, Inc. in Columbus, Indiana. Cory spent 16 years at Eli Lilly and Company in sales, market research, Lean Six Sigma, marketing analytics, and new product forecasting. He also has several years of experience in the insurance and banking industries, both as a consultant and as a manager of marketing analytics. A former US Army active duty and reserve officer, Cory was stationed in Baghdad, Iraq, in 2009 serving as the strategic advisor to the 29,000-person Iraqi Oil Police, succeeding where others failed by acquiring and delivering promised equipment to help the country secure and protect its oil infrastructure. Cory has a BBA in Aviation Administration from the University of North Dakota and a commercial helicopter license.

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.