Machine Learning With Python Cookbook: Practical Solutions from Preprocessing to
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What Stands Out
Product Details
- Practical guide with nearly 200 self-contained recipes for solving machine learning challenges
- Covers topics such as loading data, handling text or numerical data, model selection, and dimensionality reduction
- Recipes include Python code for practical application and come with discussions to provide context
- Addresses vectors, matrices, arrays, numerical and categorical data, dimensionality reduction, model evaluation, and various machine learning models
- Written by Chris Albon, a data scientist with a Ph.D. in quantitative political science and extensive experience in statistical learning and artificial intelligence
- Published by O'Reilly Media with a release date of 2018-04-30, and available in paperback format with free shipping
| ISBN-13 | 9781491989388 |
| Book Title | Machine Learning With Python Cookbook |
| UPC | Does not apply |
| ISBN | 9781491989388 |
| EAN | 9781491989388 |
| Publication Year | 2018 |
| Type | Reference |
| Format | Paperback |
| Language | English |
| Publication Name | Machine Learning with Python Cookbook |
| Item Height | 232mm |
| Author | Chris Albon |
| Publisher | O'reilly, INC International Concepts, USA |
| Item Width | 177mm |
| Subject | Writing & Reading, Engineering & Technology, Technology, Computer Science |
| Item Weight | 614g |
| Number of Pages | 366 Pages |
Who Should Buy?
-
Aspiring Data Scientists
Ideal for beginners seeking practical recipes to implement machine learning techniques using Python effectively.
-
Experienced Developers
Helpful for developers transitioning into machine learning, providing easy-to-follow solutions and code snippets.
-
Hands-on Learners
Perfect for individuals who prefer interactive learning through practical examples and real-world applications of machine learning.
-
Absolute Beginners
Not suitable for complete beginners without any programming or machine learning background, as some prior knowledge is beneficial.
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