Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning - Info and Reading Options
By Chris Albon

"Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning" was published by O'Reilly Media in Apr 01, 2018 - Beijing Boston Farnham Sebastopol Tokyo and it has 366 pages.
“Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning” Metadata:
- Title: ➤ Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning
- Author: Chris Albon
- Number of Pages: 366
- Publisher: O'Reilly Media
- Publish Date: Apr 01, 2018
- Publish Location: ➤ Beijing Boston Farnham Sebastopol Tokyo
“Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning” Subjects and Themes:
- Subjects: ➤ Machine learning - Python (computer program language) - Python (Computer program language) - Python (Langage de programmation) - COMPUTERS - Programming Languages - Python - Qa76.73.p98 a43 2018 - 005.13/3
Edition Identifiers:
- The Open Library ID: OL26832961M - OL19542254W
- Online Computer Library Center (OCLC) ID: 1019733819
- ISBN-13: 9781491989388 - 9781491989357
- ISBN-10: 1491989386
- All ISBNs: 1491989386 - 9781491989388 - 9781491989357
AI-generated Review of “Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning”:
"Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning" Description:
Open Data:
With Early Release ebooks, you get books in their earliest form--the author's raw and unedited content as he or she writes--so you can take advantage of these technologies long before the official release of these titles. You'll also receive updates when significant changes are made, new chapters are available, and the final ebook bundle is released. The Python programming language and its libraries, including pandas and scikit-learn, provide a production-grade environment to help you accomplish a broad range of machine-learning tasks. With this comprehensive cookbook, data scientists and software engineers familiar with Python will benefit from almost 200 practical recipes for building a comprehensive machine-learning pipeline--everything from data preprocessing and feature engineering to model evaluation and deep learning. Learn from author Chris Albon, a data scientist who has written more than 500 tutorials on Python, data science, and machine learning. Each recipe in this practical cookbook includes code solutions that you can put to work right away, along with a discussion of how and why they work--making it ideal as a learning tool and reference book
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