封面
版权页
Credits
About the Author
About the Reviewers
www.PacktPub.com
Support files eBooks discount offers and more
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Chapter 1. Transforming Data into Actions
A data-driven approach in business decisions
Identifying hidden patterns
Estimating the impact of an action
Summary
Chapter 2. R – A Powerful Tool for Developing Machine Learning Algorithms
Why R
The R tutorial
Some useful R packages
Summary
Chapter 3. A Simple Machine Learning Analysis
Exploring data interactively
Exploring the data using machine learning models
Predicting newer outcomes
Summary
Chapter 4. Step 1 – Data Exploration and Feature Engineering
Building a machine learning solution
Building the feature data
Exploring and visualizing the features
Modifying the features
Ranking the features using a filter or a dimensionality reduction
Summary
Chapter 5. Step 2 – Applying Machine Learning Techniques
Identifying a homogeneous group of items
Applying the k-nearest neighbor algorithm
Optimizing the k-nearest neighbor algorithm
Summary
Chapter 6. Step 3 – Validating the Results
Validating a machine learning model
Tuning the parameters
Selecting the data features to include in the model
Tuning features and parameters together
Summary
Chapter 7. Overview of Machine Learning Techniques
Overview
Supervised learning
Linear regression
Perceptron
Unsupervised learning
Summary
Chapter 8. Machine Learning Examples Applicable to Businesses
Overview of the problem
Clustering the clients
Predicting the output
Summary
Index
更新时间：2021-08-05 17:08:55
完结共60章
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