Idioma: Inglés
Publicado por Apress (edition 1st ed.), 2022
ISBN 10: 1484289773 ISBN 13: 9781484289778
Librería: BooksRun, Philadelphia, PA, Estados Unidos de America
Original o primera edición
EUR 14,34
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Añadir al carritoPaperback. Condición: Very Good. 1st ed. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 23,81
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 25,58
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Añadir al carritoCondición: As New. Unread book in perfect condition.
EUR 29,59
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Añadir al carritoPaperback. Condición: 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.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 27,27
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Librería: WorldofBooks, Goring-By-Sea, WS, Reino Unido
EUR 25,52
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Añadir al carritoPaperback. Condición: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 30,70
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Librería: California Books, Miami, FL, Estados Unidos de America
EUR 33,56
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Librería: Revaluation Books, Exeter, Reino Unido
EUR 36,67
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Añadir al carritoPaperback. Condición: Brand New. 190 pages. 9.25x6.10x0.43 inches. In Stock.
EUR 31,28
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 35,01
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EUR 35,00
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Añadir al carritoCondición: New.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 36,52
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 37,16
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: Chiron Media, Wallingford, Reino Unido
EUR 38,72
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Añadir al carritopaperback. Condición: New.
ISBN 10: 1484294130 ISBN 13: 9781484294130
Librería: Romtrade Corp., STERLING HEIGHTS, MI, Estados Unidos de America
EUR 28,90
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Añadir al carritoCondición: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.
ISBN 10: 1484294130 ISBN 13: 9781484294130
Librería: SMASS Sellers, IRVING, TX, Estados Unidos de America
EUR 30,16
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Añadir al carritoCondición: New. Brand New, Softcover edition. This item may ship from the US or our Overseas warehouse depending on your location and stock availability.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Librería: Revaluation Books, Exeter, Reino Unido
EUR 44,94
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Añadir al carritoPaperback. Condición: Brand New. 261 pages. 10.00x7.01x0.55 inches. In Stock.
ISBN 10: 1484294130 ISBN 13: 9781484294130
Librería: SMASS Sellers, IRVING, TX, Estados Unidos de America
EUR 30,49
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Añadir al carritoCondición: New. Brand New, Softcover edition. This item may ship from the US or our Overseas warehouse depending on your location and stock availability.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 71,84
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Añadir al carritoCondición: New. 1st ed. edition NO-PA16APR2015-KAP.
Idioma: Inglés
Publicado por Springer, Berlin|Apress, 2023
ISBN 10: 1484289773 ISBN 13: 9781484289778
Librería: moluna, Greven, Alemania
EUR 32,41
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Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
EUR 16,67
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Añadir al carritoPAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
EUR 26,44
Cantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: 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.
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
EUR 25,33
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Añadir al carritoHRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 55,38
Cantidad disponible: 4 disponibles
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Librería: CitiRetail, Stevenage, Reino Unido
EUR 20,68
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Añadir al carritoPaperback. Condición: 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.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 56,60
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Librería: CitiRetail, Stevenage, Reino Unido
EUR 29,55
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Añadir al carritoHardcover. Condición: new. Hardcover. 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.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 71,01
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. PRINT ON DEMAND.