Thoughtful machine learning with Python : a test-driven approach /

Gain the confidence you need to apply machine learning in your daily work. With this practical guide, author Matthew Kirk shows you how to integrate and test machine learning algorithms in your code, without the academic subtext. Featuring graphs and highlighted code examples throughout, the book fe...

Ausführliche Beschreibung

Gespeichert in:
1. Verfasser:
Kirk, Matthew (Data scientist)
Format:
Elektronisch E-Book
Sprache:
Englisch
Veröffentlicht:
Beijing : O'Reilly, 2017.
Ausgabe:
First edition.
Zusammenfassung:
Gain the confidence you need to apply machine learning in your daily work. With this practical guide, author Matthew Kirk shows you how to integrate and test machine learning algorithms in your code, without the academic subtext. Featuring graphs and highlighted code examples throughout, the book features tests with Python’s Numpy, Pandas, Scikit-Learn, and SciPy data science libraries. If you’re a software engineer or business analyst interested in data science, this book will help you: Reference real-world examples to test each algorithm through engaging, hands-on exercises Apply test-driven development (TDD) to write and run tests before you start coding Explore techniques for improving your machine-learning models with data extraction and feature development Watch out for the risks of machine learning, such as underfitting or overfitting data Work with K-Nearest Neighbors, neural networks, clustering, and other algorithms
Umfang:
1 online resource (216 pages) : color illustrations
text file
Anmerkungen:
Includes index.
Bibliografie:
Includes bibliographical references and index.
ISBN:
9781491924082
149192408X
9781491924129
1491924128
9781491924105
1491924101
Schlagworte:
Machine learning.
Python (Computer program language)
Bezugswerke:
Links: