Book Image

Advanced Machine Learning with R

By : Cory Lesmeister, Dr. Sunil Kumar Chinnamgari
Book Image

Advanced Machine Learning with R

By: Cory Lesmeister, Dr. Sunil Kumar Chinnamgari

Overview of this book

R is one of the most popular languages when it comes to exploring the mathematical side of machine learning and easily performing computational statistics. This Learning Path shows you how to leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization. You’ll work through realistic projects such as building powerful machine learning models with ensembles to predict employee attrition. Next, you’ll explore different clustering techniques to segment customers using wholesale data and even apply TensorFlow and Keras-R for performing advanced computations. Each chapter will help you implement advanced machine learning algorithms using real-world examples. You’ll also be introduced to reinforcement learning along with its use cases and models. Finally, this Learning Path will provide you with a glimpse into how some of these black box models can be diagnosed and understood. By the end of this Learning Path, you’ll be equipped with the skills you need to deploy machine learning techniques in your own projects.
Table of Contents (30 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

Philosophy behind ensembling 


Ensembling, which is super-famous among ML practitioners, can be well-understood through a simple real-world, non-ML example.

Assume that you have applied for a job in a very reputable corporate organization and you have been called for an interview. It is unlikely you will be selected for a job just based on one interview with an interviewer. In most cases, you will go through multiple rounds of interviews with several interviewers or with a panel of interviewers. The expectation from the organization is that each of the interviewers is an expert on a particular area and that the interviewer has evaluated your fitness for the job based on your experience in the interviewers' area of expertise. Your selection for the job, of course, depends on consolidated feedback from all of the interviewers that talked to you. The organization deems that you will be more successful in the job as your selection is based on a consolidated decision made by multiple experts and...