Machine Learning with Python Cookbook
Practical Solutions from Preprocessing to Deep Learning
(Sprache: Englisch)
This practical guide provides more than 200 self-contained recipes to help you solve machine learning challenges you may encounter in your work. If you're comfortable with Python and its libraries, including pandas and scikit-learn, you'll be able to...
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This practical guide provides more than 200 self-contained recipes to help you solve machine learning challenges you may encounter in your work. If you're comfortable with Python and its libraries, including pandas and scikit-learn, you'll be able to address specific problems, from loading data to training models and leveraging neural networks. Each recipe in this updated edition includes code that you can copy, paste, and run with a toy dataset to ensure that it works. From there, you can adapt these recipes according to your use case or application. Recipes include a discussion that explains the solution and provides meaningful context. Go beyond theory and concepts by learning the nuts and bolts you need to construct working machine learning applications.
Autoren-Porträt von Kyle Gallatin, Chris Albon
Kyle Gallatin is a software engineer for machine learning infrastructure with years of experience as a data analyst, data scientist and machine learning engineer. He is also a professional data science mentor, volunteer computer science teacher and frequently publishes articles at the intersection of software engineering and machine learning. Currently, Kyle is a software engineer on the machine learning platform team at Etsy.
Bibliographische Angaben
- Autoren: Kyle Gallatin , Chris Albon
- 2023, 2nd Edition, XIV, 398 Seiten, Maße: 17,5 x 22,9 cm, Kartoniert (TB), Englisch
- Verlag: O'Reilly Media
- ISBN-10: 1098135725
- ISBN-13: 9781098135720
Sprache:
Englisch
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