finelybook
R Machine Learning Projects: Implement supervised,unsupervised,and reinforcement learning techniques using R 3.5
Authors: Dr. Sunil Kumar Chinnamgari
ISBN-10 书号: 1789807948
ISBN-13 书号: 9781789807943
Publisher Finelybook 出版日期: 2019-01-14
pages 页数: 334 pages
Book Description
R is one of the most popular languages when it comes to performing computational statistics (statistical computing) easily and exploring the mathematical side of machine learning. With this book,you will leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization.
This book will help you test your knowledge and skills,guiding you on how to build easily through to complex machine learning projects. You will first learn how to build powerful machine learning models with ensembles to predict employee attrition. Next,you’ll implement a joke recommendation engine and learn how to perform sentiment analysis on Amazon reviews. You’ll also explore different clustering techniques to segment customers using wholesale data. In addition to this,the book will get you acquainted with credit card fraud detection using autoencoders,and reinforcement learning to make predictions and win on a casino slot machine.
By the end of the book,you will be equipped to confidently perform complex tasks to build research and commercial projects for automated operations.
Contents
1: EXPLORING THE MACHINE LEARNING LANDSCAPE
2: PREDICTING EMPLOYEE ATTRITION USING ENSEMBLE MODELS
3: IMPLEMENTING A JOKES RECOMMENDATION ENGINE
4: SENTIMENT ANALYSIS OF AMAZON REVIEWS WITH NLP
5: CUSTOMER SEGMENTATION USING WHOLESALE DATA
6: IMAGE RECOGNITION USING DEEP NEURAL NETWORKS
7: CREDIT CARD FRAUD DETECTION USING AUTOENCODERS
8: AUTOMATIC PROSE GENERATION WITH RECURRENT NEURAL NETWORKS
9: WINNING THE CASINO SLOT MACHINES WITH REINFORCEMENT LEARNING
What you will learn
Explore deep neural networks and various frameworks that can be used in R
Develop a joke recommendation engine to recommend jokes that match users’ tastes
Create powerful ML models with ensembles to predict employee attrition
Build autoencoders for credit card fraud detection
Work with image recognition and convolutional neural networks
Make predictions for casino slot machine using reinforcement learning
Implement NLP techniques for sentiment analysis and customer segmentation
Authors
Dr. Sunil Kumar Chinnamgari
Dr. Sunil Kumar Chinnamgari has a PhD in computer science (specializing in machine learning and natural language processing). He is an AI researcher with more than 14 years of industry experience. Currently,he works in the capacity of a lead data scientist with a US financial giant. He has published several research papers in Scopus and IEEE journals,and is a frequent speaker at various meet-ups. He is an avid coder and has won multiple hackathons. In his spare time,Sunil likes to teach,travel,and spend time with family.
