Applied Machine Learning Using Scikit-Learn and Tensorflow
Language: English
Published by Independently Published, 2026
- Softcover
- New

Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
AbeBooks seller since June 11, 1999
Condition: New
US$ 33.37
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Add to basketItem description from seller
Seller Inventory # L2-9798242864399
- Title
- Applied Machine Learning Using Scikit-Learn and Tensorflow
- Author
- Adrian Marcus
- Publisher
- Independently Published
- Publication year
- 2026
- Condition
- New
- Binding
- PAP
- Language
- English
- ISBN 13
- 9798242864399
- Item weight
- 272 grams
It is a frustrating reality for many. Most books on AI focus so much on complex math and academic theories that they forget to teach you the most important part: how to actually build something that works for a business. You end up with a "black box" that predicts numbers but can’t be explained to a boss, or a code script that is impossible to turn into a functional app.
Applied Machine Learning Using Scikit-Learn and TensorFlow is your bridge from "student" to "professional engineer." This book isn't about memorizing formulas; it’s about getting your hands dirty. We take you on a journey from cleaning messy data with Scikit-Learn to building powerful "brains" with TensorFlow. You won't just learn to code; you’ll learn to deploy your models as live APIs, secure them with modern MLOps, and even make them explainable so people actually trust your results.
By the time you finish, you’ll have the confidence to build real-world prediction systems—from stock market analysis to image recognition—that are stable, ethical, and ready for production. Whether you are a curious Python fan or an aspiring engineer, this is your roadmap to mastering the tools that are currently shaping our future.
Stop guessing and start building. Scroll up and grab your copy today to turn your AI ideas into reality!
"Synopsis" may belong to another edition of this title.
PBShop.store UK
Fairford, GLOS, United Kingdom
AbeBooks seller since June 11, 1999
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