关于此电子书
Aimed for intermediate-to-advanced people (especially data scientist) who are already into the field of data science
What You Will LearnGet to grips with R techniques to clean and prepare your data for analysis, and visualize your resultsImplement R machine learning algorithms from scratch and be amazed to see the algorithms in actionSolve interesting real-world problems using machine learning and R as the journey unfoldsWrite reusable code and build complete machine learning systems from the ground upLearn specialized machine learning techniques for text mining, social network data, big data, and moreDiscover the different types of machine learning models and learn which is best to meet your data needs and solve your analysis problemsEvaluate and improve the performance of machine learning modelsLearn specialized machine learning techniques for text mining, social network data, big data, and moreIn DetailR 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:
R Machine Learning By Example By Raghav Bali, Dipanjan SarkarMachine Learning with R Learning - Second Edition By Brett LantzMastering Machine Learning with R By Cory LesmeisterStyle and approachThis is an enticing learning path that starts from the very basics to gradually pick up pace as the story unfolds. Each concept is first defined in the larger context of things succinctly, followed by a detailed explanation of their application. Each topic is explained with the help of a project that solves a real-world problem involving hands-on work thus giving you a deep insight into the world of machine learning.
作者简介
Raghav Bali has a master's degree (gold medalist) in IT from the International Institute of Information Technology, Bangalore. He is an IT engineer at Intel, the world's largest silicon company, where he works on analytics, business intelligence, and application development. He has worked as an analyst and developer in domains such as ERP, finance, and BI with some of the top companies in the world.
Dipanjan Sarkar is an IT engineer at Intel, the world's largest silicon company, where he works on analytics, business intelligence, and application development. He received his master's degree in information technology from the International Institute of Information Technology, Bangalore. His areas of specialization include software engineering, data science, machine learning, and text analytics. Dipanjan's interests include learning about new technology, disruptive start-ups, and data science.
Brett Lantz has spent more than 10 years using innovative data methods to understand human behavior. A trained sociologist, he was first enchanted by machine learning while studying a large database of teenagers' social networking website profiles.
