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Condition: New.
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Applied Recommender Systems with Python
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: New. 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 systemsWho This Book Is ForData scientists, machine learning engineers, and Python programmers interested in building and implementing recommender systems to solve problems.
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Condition: As New. Unread book in perfect condition.
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Time Series Algorithms Recipes: Implement Machine Learning and Deep Learning Techniques with Python
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
First Edition
Condition: New. 2022. 1st ed. paperback. . . . . .
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Add to basketPaperback. Condition: Brand New. 190 pages. 9.25x6.10x0.43 inches. In Stock.
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Time Series Algorithms Recipes: Implement Machine Learning and Deep Learning Techniques with Python
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
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Time Series Algorithms Recipes 1st ed.
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 36.84
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Condition: New. 2022. 1st ed. paperback. . . . . . Books ship from the US and Ireland.
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Time Series Algorithms Recipes 1st ed.
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 40.51
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Applied Recommender Systems with Python : Build Recommender Systems with Deep Learning, NLP and Graph-Based Techniques
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 41.99
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Applied Recommender Systems with Python : Build Recommender Systems with Deep Learning, NLP and Graph-Based Techniques
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 43.69
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Add to basketpaperback. Condition: New.
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Applied Recommender Systems with Python: Build Recommender Systems with Deep Learning, NLP and Graph-Based Techniques
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
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Add to basketPaperback. Condition: Brand New. 261 pages. 10.00x7.01x0.55 inches. In Stock.
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Condition: New. 1st ed. edition NO-PA16APR2015-KAP.
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PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Time Series Algorithms Recipes
Language: English
Published by Springer, Berlin|Apress, 2023
ISBN 10: 1484289773 ISBN 13: 9781484289778
Condition: New.
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Taschenbuch. Condition: Neu. Neuware - Drowning in the digital noise This isn't another preachy self-help book. It's not a spiritual sermon wrapped in Sanskrit, and definitely not about quitting social media to live in a cave.
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Lost in the Scroll
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
US$ 19.59
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Ships from United Kingdom to U.S.A.Quantity: Over 20 available
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.
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Buch. Condition: Neu. Neuware - Drowning in the digital noise This isn't another preachy self-help book. It's not a spiritual sermon wrapped in Sanskrit, and definitely not about quitting social media to live in a cave.
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US$ 85.79 shipping
Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketPaperback. Condition: New. 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 systemsWho This Book Is ForData scientists, machine learning engineers, and Python programmers interested in building and implementing recommender systems to solve problems.
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HRD. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Lost in the Scroll
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
US$ 29.54
US$ 5.49 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketHRD. 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.
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US$ 23.77
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Add to basketPaperback. Condition: new. Paperback. Drowning in the digital noise? This isn't another preachy self-help book. It's not a spiritual sermon wrapped in Sanskrit, and definitely not about quitting social media to live in a cave.Lost in the Scroll is your no-fluff reality check for the digital age. It's where ancient Indian wisdom, yes, Sanatan Dharma, quietly shows up in your everyday chaos, whether you realize it or not.From doomscrolling to dopamine burnout, this book connects the dots between timeless truths and your hyper-online life. No robes, no rituals - just real talk on purpose, peace, and presence in a world designed to distract you.You don't have to ditch your phone.But you might want to rethink what you're really searching for when you scroll.Old wisdom. New context.No preaching. Just perspective. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Condition: New. Print on Demand.
