This book will teach you how to build recommender systems with machine learning algorithms using Python. Recommender systems have become an essential part of every internet-based business today. You'll start by learning basic concepts of recommender systems, with an overview of different types of recommender engines and how they function. Next, you will see how to build recommender systems with traditional algorithms such as market basket analysis and content- and knowledge-based recommender systems with NLP. The authors ...
Read More
This book will teach you how to build recommender systems with machine learning algorithms using Python. Recommender systems have become an essential part of every internet-based business today. You'll start by learning basic concepts of recommender systems, with an overview of different types of recommender engines and how they function. Next, you will see how to build recommender systems with traditional algorithms such as market basket analysis and content- and knowledge-based recommender systems with NLP. The authors then demonstrate techniques such as collaborative filtering using matrix factorization and hybrid recommender systems that incorporate both content-based and collaborative filtering techniques. This is followed by a tutorial on building machine learning-based recommender systems using clustering and classification algorithms like K-means and random forest. The last chapters cover NLP, deep learning, and graph-based techniques to build a recommender engine. Each chapter includes data preparation, multiple ways to evaluate and optimize the recommender systems, supporting examples, and illustrations. By the end of this book, you will understand and be able to build recommender systems with various tools and techniques with machine learning, deep learning, and graph-based algorithms. What You Will Learn Understand and implement different recommender systems techniques with Python Employ popular methods like content- and knowledge-based, collaborative filtering, market basket analysis, and matrix factorization Build hybrid recommender systems that incorporate both content-based and collaborative filtering Leverage machine learning, NLP, and deep learning for building recommender systems Who This Book Is For Data scientists, machine learning engineers, and Python programmers interested in building and implementing recommender systems to solve problems.
Read Less
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
Very good. Simply Brit – welcome to our online used book store, where affordability meets great quality. Dive into a world of captivating reads without breaking the bank. We take pride in offering a wide selection of used books, from classics to hidden gems, ensuring there's something for every literary palate. All orders are shipped within 24 hours and our lightning fast-delivery within 48 hours coupled with our prompt customer service ensures a smooth journey from ordering to delivery. Discover the joy of reading with us, your trusted source for affordable books that do not compromise on quality.
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
New. Trade paperback (US). Glued binding. 248 p. Contains: Unspecified, Illustrations, black & white, Illustrations, color. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
New. Trade paperback (US). Glued binding. 248 p. Contains: Unspecified, Illustrations, black & white, Illustrations, color. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
New in New jacket. Applied Recommender Systems with Python: Build Recommender Systems with Deep Learning, Nlp and Graph-Based Techniques (Paperback or Softback)
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
Fine. Trade paperback (US). Glued binding. 248 p. Contains: Unspecified, Illustrations, black & white, Illustrations, color. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
