目錄(60章)
倒序
- 封面
- 版權(quán)頁
- 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 更新時(shí)間：2021-08-05 17:08:55
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