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Machine Learning: a Concise Introduction (Wiley Series in Probability and Statistics)
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Machine Learning: a Concise Introduction offers a comprehensive introduction to the core concepts, approaches, and applications of machine learning.
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Product Details
- Comprehensive introduction to core concepts, approaches, and applications of machine learning
- Emphasizes design principles and their influence on the design of ensemble methods
- Includes methods for optimization, risk estimation, and model selection
- Presents R source code demonstrating application and interpretation of techniques
- Contains exercises with selected solutions and useful information for effectively communicating with clients
- Authored by Steven W. Knox, an expert with over twenty years' experience in using machine learning, statistics, and mathematics to solve real-world problems
| Publisher | Wiley |
| Publication date | March 30, 2018 |
| Edition | 1st |
| Language | English |
| Print length | 346 pages |
| ISBN-10 | 1119439191 |
| ISBN-13 | 978-1119439196 |
| Item Weight | 1 pounds (450 grams) |
| Dimensions | 6.24 x 1.01 x 9.24 inches (15.8 x 2.6 x 23.5 cm) |
| Part of series | Wiley Series in Probability and Statistics |
Product Description
Machine Learning: a Concise Introduction (Wiley Series in Probability and Statistics)
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Features & Benefits
- Comprehensive introduction to the core concepts, approaches, and applications of machine learning.
- Includes fundamental ideas, terminology, and techniques for solving applied problems.
- Provides R source code which shows how to apply and interpret many of the techniques covered.
- Includes methods for optimization, risk estimation, and model selection.
- Contains useful information for effectively communicating with clients.
- Written by an expert with over twenty years’ experience in using Machine Learning.
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