Description: Title: Applied Recommender Systems with Python: Build Recommender Systems with Deep Learning, Nlp and Graph-Based Techniques Author: Kulkarni, Akshay Publisher: Apress Binding: Paperback Pages: 248 Dimensions: 10.00h x 7.00w x 0.55d Product Weight: 1.02 lbs. Language: English ISBN: 9781484289532 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 LearnUnderstand and implement different recommender systems techniques with PythonEmploy 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 filteringLeverage machine learning, NLP, and deep learning for building recommender systems Who This Book Is ForData scientists, machine learning engineers, and Python programmers interested in building and implementing recommender systems to solve problems. Ships Fast From The USA! Authorized Dealer
Price: 43.99 USD
Location: Tennessee
End Time: 2025-01-02T01:03:00.000Z
Shipping Cost: 9.95 USD
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Restocking Fee: No
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money Back
Book Title: Apress
Number of Pages: Xiii, 248 Pages
Language: English
Publication Name: Applied Recommender Systems with Python : Build Recommender Systems with Deep Learning, NLP and Graph-Based Techniques
Publisher: Apress L. P.
Publication Year: 2022
Subject: Intelligence (Ai) & Semantics, Probability & Statistics / General, Programming Languages / Python
Item Weight: 17.9 Oz
Type: Textbook
Subject Area: Mathematics, Computers
Item Length: 10 in
Author: V. Adithya Krishnan, Akshay Kulkarni, Anoosh Kulkarni, Adarsha Shivananda
Item Width: 7 in
Format: Trade Paperback
