Practical Machine Learning Cookbook
Machine learning is the new BLACK GOLD. In this book, we explore topics such as classification, clustering, model selection and regularization, nonlinearity, supervised, unsupervised, and reinforcement learning, structured prediction, neural networks, deep learning, and case studies. The algorithms are developed using R.The book is for students and professionals in the field of statistics, data analytics, and computer science.
Offered by
Difficulty Level
Intermediate
Completion Time
19h
Language
English
About Book
Who Is This Book For?
This book is for analysts, statisticians, and data scientists with knowledge of fundamentals of machine learning and statistics, who need help in dealing with challenging scenarios faced every day of working in the field of machine learning and improving system performance and accuracy. It is assumed that as a reader you have a good understanding of mathematics. Working knowledge of R is expected.
Practical Machine Learning Cookbook
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 19h total length
Introduction
Classification
Clustering
Model Selection and Regularization
Non-linearity
Supervised Learning
Unsupervised Learning
Reinforcement learning
Structured prediction
Neural Networks
Deep Learning
Case Study 1
Case Study 2
Case Study 3
Related Resources
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