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Machine Learning: Make Your Own Recommender System (Learn Machine Learning with Python for Beginners) - Softcover

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9781726769037: Machine Learning: Make Your Own Recommender System (Learn Machine Learning with Python for Beginners)

Synopsis

Want to code your own recommender system from scratch and learn machine learning theory at the same time?

Recommender systems power the platforms we use every day—Amazon, Netflix, Spotify, and more. But how do they really work? In Machine Learning: Make Your Own Recommender System, Oliver Theobald walks you through one of the most practical and fascinating applications of machine learning: personalized recommendations.

Using Python, real-world datasets, and the beginner-friendly Scikit-learn library, you’ll not only learn the theory behind collaborative filtering, content-based filtering, and hybrid approaches, but also implement them yourself—step by step.

What you’ll learn:

- The essential principles behind recommender systems
- How to set up your Python environment with Jupyter Notebook
- The difference between user-based and item-based filtering
- How to apply Singular Value Decomposition (SVD) and Naive Bayes
- Why recommendation algorithms shape online behavior—and how to build your own

This book is perfect for:

- Readers of Machine Learning for Absolute Beginners or Oliver's other data science books
- Beginners looking to learn machine learning in a hands-on way
- Readers who found the Machine Learning for Dummies book too vague
- Anyone exploring recommender system design or building portfolio projects

If you've always wanted to understand the real mechanics behind what “You might also like…” really means, this is the book for you! No PhD required—just curiosity, a computer, and the willingness to learn by doing!

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Theobald, Oliver
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Paperback. Condition: new. Paperback. Want to code your own recommender system from scratch and learn machine learning theory at the same time?Recommender systems power the platforms we use every day-Amazon, Netflix, Spotify, and more. But how do they really work? In Machine Learning: Make Your Own Recommender System, Oliver Theobald walks you through one of the most practical and fascinating applications of machine learning: personalized recommendations.Using Python, real-world datasets, and the beginner-friendly Scikit-learn library, you'll not only learn the theory behind collaborative filtering, content-based filtering, and hybrid approaches, but also implement them yourself-step by step.What you'll learn: - The essential principles behind recommender systems- How to set up your Python environment with Jupyter Notebook- The difference between user-based and item-based filtering- How to apply Singular Value Decomposition (SVD) and Naive Bayes- Why recommendation algorithms shape online behavior-and how to build your ownThis book is perfect for: - Readers of Machine Learning for Absolute Beginners or Oliver's other data science books- Beginners looking to learn machine learning in a hands-on way- Readers who found the Machine Learning for Dummies book too vague- Anyone exploring recommender system design or building portfolio projectsIf you've always wanted to understand the real mechanics behind what "You might also like." really means, this is the book for you! No PhD required-just curiosity, a computer, and the willingness to learn by doing! Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781726769037

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paperback. Condition: Very Good. Machine Learning: Make Your Own Recommender System: 3 (Learn Machine Learning with Python Books for Beginners) This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. . Seller Inventory # 7719-9781726769037

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