9781394155378 - applied machine learning for data science practitioners di subramanian, vidya (17 risultati)

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Da: INDOO, Avenel, NJ, U.S.A.INDOO
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EUR 61,60
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New. Brand New.

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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
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EUR 62,96
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HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

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Da: Basi6 International, Irving, TX, U.S.A.Basi6 International
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EUR 72,12
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Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

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Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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EUR 76,16
Spedizione gratuitaSpedito in U.S.A.Quantità: 1 disponibili
Hardcover. Condizione: new. Hardcover. A single-volume reference on data science techniques for evaluating and solving business problems using Applied Machine Learning (ML). "This book provides an excellent, practical compendium of the foundational topics in data science and machine learning, from a true expert. This book shows…how Data Science and Machine Learning fit together in a workflow and learning that workflow is an essential foundation for building ML systems. I highly recommend this book for anyone who wants to master the fundamentals of building and analyzing ML models."Dr Anoop Sinha, Research Director, Google Applied Machine Learning for Data Science Practitioners offers a practical, step-by-step guide to building end-to-end ML solutions for real-world business challenges, empowering data science practitioners to make informed decisions and select the right techniques for any use case. Unlike many data science books that focus on popular algorithms and coding, this book takes a holistic approach. It equips you with the knowledge to evaluate a range of techniques and algorithms. The book balances theoretical concepts with practical examples to illustrate key concepts, derive insights, and demonstrate applications. In addition to code snippets and reviewing output, the book provides guidance on interpreting results. This book is an essential resource if you are looking to elevate your understanding of ML and your technical capabilities, combining theoretical and practical coding examples. A basic understanding of using data to solve business problems, high school-level math and statistics, and basic Python coding skills are assumed. Written by a recognized data science expert, Applied Machine Learning for Data Science Practitioners covers essential topics, including: Data Science Fundamentals that provide you with an overview of core concepts, laying the foundation for understanding ML.Data Preparation covers the process of framing ML problems and preparing data and features for modeling.ML Problem Solving introduces you to a range of ML algorithms, including Regression, Classification, Ranking, Clustering, Patterns, Time Series, and Anomaly Detection.Model Optimization explores frameworks, decision trees, and ensemble methods to enhance performance and guide the selection of the most effective model.ML Ethics addresses ethical considerations, including fairness, accountability, transparency, and ethics.Model Deployment and Monitoring focuses on production deployment, performance monitoring, and adapting to model drift. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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EUR 63,32
EUR 11,00 spedizioneSpedito da Italia a U.S.A.Quantità: Più di 20 disponibili
Condizione: new.

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Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
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EUR 81,94
Spedizione gratuitaSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Hardback. Condizione: New. A single-volume reference on data science techniques for evaluating and solving business problems using Applied Machine Learning (ML). Applied Machine Learning for Data Science Practitioners offers a practical, step-by-step guide to building end-to-end ML solutions for real-world business challenges, e…mpowering data science practitioners to make informed decisions and select the right techniques for any use case. Unlike many data science books that focus on popular algorithms and coding, this book takes a holistic approach. It equips you with the knowledge to evaluate a range of techniques and algorithms. The book balances theoretical concepts with practical examples to illustrate key concepts, derive insights, and demonstrate applications. In addition to code snippets and reviewing output, the book provides guidance on interpreting results. This book is an essential resource if you are looking to elevate your understanding of ML and your technical capabilities, combining theoretical and practical coding examples. A basic understanding of using data to solve business problems, high school-level math and statistics, and basic Python coding skills are assumed. Written by a recognized data science expert, Applied Machine Learning for Data Science Practitioners covers essential topics, including: Data Science Fundamentals that provide you with an overview of core concepts, laying the foundation for understanding ML.Data Preparation covers the process of framing ML problems and preparing data and features for modeling.ML Problem Solving introduces you to a range of ML algorithms, including Regression, Classification, Ranking, Clustering, Patterns, Time Series, and Anomaly Detection.Model Optimization explores frameworks, decision trees, and ensemble methods to enhance performance and guide the selection of the most effective model.ML Ethics addresses ethical considerations, including fairness, accountability, transparency, and ethics.Model Deployment and Monitoring focuses on production deployment, performance monitoring, and adapting to model drift.

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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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EUR 83,73
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Condizione: New.

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Da: Majestic Books, Hounslow, , Regno UnitoMajestic Books
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EUR 81,35
EUR 7,54 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 3 disponibili
Condizione: New.

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Da: Ubiquity Trade, Miami, FL, U.S.A.Ubiquity Trade
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EUR 91,35
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Condizione: New. Brand new! Please provide a physical shipping address.

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Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
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EUR 82,61
EUR 10,50 spedizioneSpedito da Irlanda a U.S.A.Quantità: Più di 20 disponibili
Condizione: New.

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Da: THE SAINT BOOKSTORE, Southport, , Regno UnitoTHE SAINT BOOKSTORE
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EUR 73,85
EUR 25,09 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.

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Da: Revaluation Books, Exeter, , Regno UnitoRevaluation Books
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EUR 88,20
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Hardcover. Condizione: Brand New. 656 pages. 11.02x11.02x2.36 inches. In Stock.

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Da: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
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EUR 102,38
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Condizione: New.

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- Edizione Internazionale
Da: UK BOOKS STORE, London, LONDO, Regno UnitoUK BOOKS STORE
Contatta il venditoreVenditore con 5 stelleEdizione InternazionaleCondizione: Nuovo
EUR 123,90
EUR 3,47 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 3 disponibili
Condizione: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if t…he Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.

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Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 88,94
EUR 42,89 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Hardcover. Condizione: new. Hardcover. A single-volume reference on data science techniques for evaluating and solving business problems using Applied Machine Learning (ML). "This book provides an excellent, practical compendium of the foundational topics in data science and machine learning, from a true expert. This book shows…how Data Science and Machine Learning fit together in a workflow and learning that workflow is an essential foundation for building ML systems. I highly recommend this book for anyone who wants to master the fundamentals of building and analyzing ML models."Dr Anoop Sinha, Research Director, Google Applied Machine Learning for Data Science Practitioners offers a practical, step-by-step guide to building end-to-end ML solutions for real-world business challenges, empowering data science practitioners to make informed decisions and select the right techniques for any use case. Unlike many data science books that focus on popular algorithms and coding, this book takes a holistic approach. It equips you with the knowledge to evaluate a range of techniques and algorithms. The book balances theoretical concepts with practical examples to illustrate key concepts, derive insights, and demonstrate applications. In addition to code snippets and reviewing output, the book provides guidance on interpreting results. This book is an essential resource if you are looking to elevate your understanding of ML and your technical capabilities, combining theoretical and practical coding examples. A basic understanding of using data to solve business problems, high school-level math and statistics, and basic Python coding skills are assumed. Written by a recognized data science expert, Applied Machine Learning for Data Science Practitioners covers essential topics, including: Data Science Fundamentals that provide you with an overview of core concepts, laying the foundation for understanding ML.Data Preparation covers the process of framing ML problems and preparing data and features for modeling.ML Problem Solving introduces you to a range of ML algorithms, including Regression, Classification, Ranking, Clustering, Patterns, Time Series, and Anomaly Detection.Model Optimization explores frameworks, decision trees, and ensemble methods to enhance performance and guide the selection of the most effective model.ML Ethics addresses ethical considerations, including fairness, accountability, transparency, and ethics.Model Deployment and Monitoring focuses on production deployment, performance monitoring, and adapting to model drift. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 76,44
EUR 75,35 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Hardback. Condizione: New. A single-volume reference on data science techniques for evaluating and solving business problems using Applied Machine Learning (ML). Applied Machine Learning for Data Science Practitioners offers a practical, step-by-step guide to building end-to-end ML solutions for real-world business challenges, e…mpowering data science practitioners to make informed decisions and select the right techniques for any use case. Unlike many data science books that focus on popular algorithms and coding, this book takes a holistic approach. It equips you with the knowledge to evaluate a range of techniques and algorithms. The book balances theoretical concepts with practical examples to illustrate key concepts, derive insights, and demonstrate applications. In addition to code snippets and reviewing output, the book provides guidance on interpreting results. This book is an essential resource if you are looking to elevate your understanding of ML and your technical capabilities, combining theoretical and practical coding examples. A basic understanding of using data to solve business problems, high school-level math and statistics, and basic Python coding skills are assumed. Written by a recognized data science expert, Applied Machine Learning for Data Science Practitioners covers essential topics, including: Data Science Fundamentals that provide you with an overview of core concepts, laying the foundation for understanding ML.Data Preparation covers the process of framing ML problems and preparing data and features for modeling.ML Problem Solving introduces you to a range of ML algorithms, including Regression, Classification, Ranking, Clustering, Patterns, Time Series, and Anomaly Detection.Model Optimization explores frameworks, decision trees, and ensemble methods to enhance performance and guide the selection of the most effective model.ML Ethics addresses ethical considerations, including fairness, accountability, transparency, and ethics.Model Deployment and Monitoring focuses on production deployment, performance monitoring, and adapting to model drift.

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Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 133,10
EUR 32,38 spedizioneSpedito da Australia a U.S.A.Quantità: 1 disponibili
Hardcover. Condizione: new. Hardcover. A single-volume reference on data science techniques for evaluating and solving business problems using Applied Machine Learning (ML). "This book provides an excellent, practical compendium of the foundational topics in data science and machine learning, from a true expert. This book shows…how Data Science and Machine Learning fit together in a workflow and learning that workflow is an essential foundation for building ML systems. I highly recommend this book for anyone who wants to master the fundamentals of building and analyzing ML models."Dr Anoop Sinha, Research Director, Google Applied Machine Learning for Data Science Practitioners offers a practical, step-by-step guide to building end-to-end ML solutions for real-world business challenges, empowering data science practitioners to make informed decisions and select the right techniques for any use case. Unlike many data science books that focus on popular algorithms and coding, this book takes a holistic approach. It equips you with the knowledge to evaluate a range of techniques and algorithms. The book balances theoretical concepts with practical examples to illustrate key concepts, derive insights, and demonstrate applications. In addition to code snippets and reviewing output, the book provides guidance on interpreting results. This book is an essential resource if you are looking to elevate your understanding of ML and your technical capabilities, combining theoretical and practical coding examples. A basic understanding of using data to solve business problems, high school-level math and statistics, and basic Python coding skills are assumed. Written by a recognized data science expert, Applied Machine Learning for Data Science Practitioners covers essential topics, including: Data Science Fundamentals that provide you with an overview of core concepts, laying the foundation for understanding ML.Data Preparation covers the process of framing ML problems and preparing data and features for modeling.ML Problem Solving introduces you to a range of ML algorithms, including Regression, Classification, Ranking, Clustering, Patterns, Time Series, and Anomaly Detection.Model Optimization explores frameworks, decision trees, and ensemble methods to enhance performance and guide the selection of the most effective model.ML Ethics addresses ethical considerations, including fairness, accountability, transparency, and ethics.Model Deployment and Monitoring focuses on production deployment, performance monitoring, and adapting to model drift. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.