This book is a useful textbook for graduate students and is a reference book for researchers and machine learning and big data practitioners who want to know how to deal with large amounts of data and the main problems that arise in both the development of predictive models and the application of machine learning algorithms. It covers fundamental modern topics in machine learning and describes several key aspects of the application of algorithms. The book is focused on credit risk and the financial crisis, so it could also be interesting for researchers in that field.
Machine Learning with R Quick Start Guide
By :
Machine Learning with R Quick Start Guide
By:
Overview of this book
Machine Learning with R Quick Start Guide takes you on a data-driven journey that starts with the very basics of R and machine learning. It gradually builds upon core concepts so you can handle the varied complexities of data and understand each stage of the machine learning pipeline.
From data collection to implementing Natural Language Processing (NLP), this book covers it all. You will implement key machine learning algorithms to understand how they are used to build smart models. You will cover tasks such as clustering, logistic regressions, random forests, support vector machines, and more. Furthermore, you will also look at more advanced aspects such as training neural networks and topic modeling.
By the end of the book, you will be able to apply the concepts of machine learning, deal with data-related problems, and solve them using the powerful yet simple language that is R.
Related Content you might be interested in
Current Title:
Machine Learning with R Quick Start Guide
Table of Contents (9 chapters)
Preface
Free Chapter
R Fundamentals for Machine Learning
Predicting Failures of Banks - Data Collection
Predicting Failures of Banks - Descriptive Analysis
Predicting Failures of Banks - Univariate Analysis
Predicting Failures of Banks - Multivariate Analysis
Visualizing Economic Problems in the European Union
Sovereign Crisis - NLP and Topic Modeling
Other Books You May Enjoy
Customer Reviews