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Add to basketPaperback. Condition: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less 0.7.
Published by Packt Publishing, Limited, 2018
ISBN 10: 1788993756 ISBN 13: 9781788993753
Language: English
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Add to basketCondition: very_good. Gently read. May have name of previous ownership, or ex-library edition. Binding tight; spine straight and smooth, with no creasing; covers clean and crisp. Minimal signs of handling or shelving. 100% GUARANTEE! Shipped with delivery confirmation, if youâre not satisfied with purchase please return item for full refund. Ships USPS Media Mail.
Published by Packt Publishing 2018-07, 2018
ISBN 10: 1788993756 ISBN 13: 9781788993753
Language: English
Seller: Chiron Media, Wallingford, United Kingdom
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Published by Packt Publishing Limited, GB, 2018
ISBN 10: 1788993756 ISBN 13: 9781788993753
Language: English
Seller: Rarewaves.com UK, London, United Kingdom
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Add to basketPaperback. Condition: New. With Hands-On Recommendation Systems with Python, learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the webKey FeaturesBuild industry-standard recommender systemsOnly familiarity with Python is requiredNo need to wade through complicated machine learning theory to use this bookBook DescriptionRecommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether it's friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This book shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory-you'll get started with building and learning about recommenders as quickly as possible.In this book, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You'll use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques With this book, all you need to get started with building recommendation systems is a familiarity with Python, and by the time you're fnished, you will have a great grasp of how recommenders work and be in a strong position to apply the techniques that you will learn to your own problem domains.What you will learnGet to grips with the different kinds of recommender systemsMaster data-wrangling techniques using the pandas libraryBuilding an IMDB Top 250 CloneBuild a content based engine to recommend movies based on movie metadataEmploy data-mining techniques used in building recommendersBuild industry-standard collaborative filters using powerful algorithmsBuilding Hybrid Recommenders that incorporate content based and collaborative flteringWho this book is forIf you are a Python developer and want to develop applications for social networking, news personalization or smart advertising, this is the book for you. Basic knowledge of machine learning techniques will be helpful, but not mandatory.
Published by Packt Publishing 7/27/2018, 2018
ISBN 10: 1788993756 ISBN 13: 9781788993753
Language: English
Seller: BargainBookStores, Grand Rapids, MI, U.S.A.
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Add to basketPaperback or Softback. Condition: New. Hands-On Recommendation Systems with Python 0.58. Book.
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Add to basketCondition: New. Recommendation systems are at the heart of almost every internet business today from Facebook to Netflix to Amazon. Providing good recommendations, whether it s friends, movies or groceries, goes a long way in defining user experience and enticing your cus.
Published by Packt Publishing Limited, GB, 2018
ISBN 10: 1788993756 ISBN 13: 9781788993753
Language: English
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
£ 36.69
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Add to basketPaperback. Condition: New. With Hands-On Recommendation Systems with Python, learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the webKey FeaturesBuild industry-standard recommender systemsOnly familiarity with Python is requiredNo need to wade through complicated machine learning theory to use this bookBook DescriptionRecommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether it's friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This book shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory-you'll get started with building and learning about recommenders as quickly as possible.In this book, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You'll use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques With this book, all you need to get started with building recommendation systems is a familiarity with Python, and by the time you're fnished, you will have a great grasp of how recommenders work and be in a strong position to apply the techniques that you will learn to your own problem domains.What you will learnGet to grips with the different kinds of recommender systemsMaster data-wrangling techniques using the pandas libraryBuilding an IMDB Top 250 CloneBuild a content based engine to recommend movies based on movie metadataEmploy data-mining techniques used in building recommendersBuild industry-standard collaborative filters using powerful algorithmsBuilding Hybrid Recommenders that incorporate content based and collaborative flteringWho this book is forIf you are a Python developer and want to develop applications for social networking, news personalization or smart advertising, this is the book for you. Basic knowledge of machine learning techniques will be helpful, but not mandatory.
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Published by Packt Publishing Limited, 2018
ISBN 10: 1788993756 ISBN 13: 9781788993753
Language: English
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
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Add to basketPAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Published by Packt Publishing Limited, 2018
ISBN 10: 1788993756 ISBN 13: 9781788993753
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
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Add to basketPaperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 100.
Published by Packt Publishing Limited, 2018
ISBN 10: 1788993756 ISBN 13: 9781788993753
Language: English
Seller: PBShop.store US, Wood Dale, IL, U.S.A.
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Add to basketPAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Published by Packt Publishing, Limited, 2018
ISBN 10: 1788993756 ISBN 13: 9781788993753
Language: English
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New. Print on Demand.
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.