Mastering Machine Learning Scikit Learn by Hackeling Gavin (21 results)
- Softcover
Seller: Bay State Book Company, North Smithfield, RI, U.S.A.Bay State Book Company
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- Softcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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- Softcover
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Paperback or Softback. Condition: New. Mastering Machine Learning with scikit-learn, Second Edition. Book.
- Softcover
Seller: California Books, Miami, FL, U.S.A.California Books
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- Softcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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- Softcover
Seller: Rarewaves.com USA, London, LONDO, United KingdomRarewaves.com USA
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Digital. Condition: New. Use scikit-learn to apply machine learning to real-world problemsAbout This Book. Master popular machine learning models including k-nearest neighbors, random forests, logistic regression, k-means, naive Bayes, and artificial neural networks. Learn how to build and evaluate performance of efficient model…s using scikit-learn. Practical guide to master your basics and learn from real life applications of machine learningWho This Book Is ForThis book is intended for software engineers who want to understand how common machine learning algorithms work and develop an intuition for how to use them, and for data scientists who want to learn about the scikit-learn API. Familiarity with machine learning fundamentals and Python are helpful, but not required. What You Will Learn. Review fundamental concepts such as bias and variance. Extract features from categorical variables, text, and images. Predict the values of continuous variables using linear regression and K Nearest Neighbors. Classify documents and images using logistic regression and support vector machines. Create ensembles of estimators using bagging and boosting techniques. Discover hidden structures in data using K-Means clustering. Evaluate the performance of machine learning systems in common tasksIn DetailMachine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. Using powerful algorithms and techniques offered by machine learning you can automate any analytical model.This book examines a variety of machine learning models including popular machine learning algorithms such as k-nearest neighbors, logistic regression, naive Bayes, k-means, decision trees, and artificial neural networks. It discusses data preprocessing, hyperparameter optimization, and ensemble methods. You will build systems that classify documents, recognize images, detect ads, and more. You will learn to use scikit-learn's API to extract features from categorical variables, text and images; evaluate model performance, and develop an intuition for how to improve your model's performance.By the end of this book, you will master all required concepts of scikit-learn to build efficient models at work to carry out advanced tasks with the practical approach.Style and approachThis book is motivated by the belief that you do not understand something until you can describe it simply. Work through toy problems to develop your understanding of the learning algorithms and models, then apply your learnings to real-life problems.
- Softcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condition: New. pp. 254.
- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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£ 44.65
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- Softcover
Seller: Chiron Media, Wallingford, United KingdomChiron Media
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£ 41.47
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Paperback. Condition: New.
- Softcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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£ 43.95
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- Softcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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£ 48.35
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Condition: As New. Unread book in perfect condition.
- Softcover
Seller: Phatpocket Limited, Waltham Abbey, HERTS, United KingdomPhatpocket Limited
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£ 88.95
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Condition: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.
- Softcover
Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
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£ 45.21
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Digital. Condition: New. Use scikit-learn to apply machine learning to real-world problemsAbout This Book. Master popular machine learning models including k-nearest neighbors, random forests, logistic regression, k-means, naive Bayes, and artificial neural networks. Learn how to build and evaluate performance of efficient model…s using scikit-learn. Practical guide to master your basics and learn from real life applications of machine learningWho This Book Is ForThis book is intended for software engineers who want to understand how common machine learning algorithms work and develop an intuition for how to use them, and for data scientists who want to learn about the scikit-learn API. Familiarity with machine learning fundamentals and Python are helpful, but not required. What You Will Learn. Review fundamental concepts such as bias and variance. Extract features from categorical variables, text, and images. Predict the values of continuous variables using linear regression and K Nearest Neighbors. Classify documents and images using logistic regression and support vector machines. Create ensembles of estimators using bagging and boosting techniques. Discover hidden structures in data using K-Means clustering. Evaluate the performance of machine learning systems in common tasksIn DetailMachine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. Using powerful algorithms and techniques offered by machine learning you can automate any analytical model.This book examines a variety of machine learning models including popular machine learning algorithms such as k-nearest neighbors, logistic regression, naive Bayes, k-means, decision trees, and artificial neural networks. It discusses data preprocessing, hyperparameter optimization, and ensemble methods. You will build systems that classify documents, recognize images, detect ads, and more. You will learn to use scikit-learn's API to extract features from categorical variables, text and images; evaluate model performance, and develop an intuition for how to improve your model's performance.By the end of this book, you will master all required concepts of scikit-learn to build efficient models at work to carry out advanced tasks with the practical approach.Style and approachThis book is motivated by the belief that you do not understand something until you can describe it simply. Work through toy problems to develop your understanding of the learning algorithms and models, then apply your learnings to real-life problems.
- Softcover
Seller: Mispah books, Redhill, SURRE, United KingdomMispah books
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£ 234.00
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Paperback. Condition: Good. Good. Dust Jacket NOT present. CD WILL BE MISSING. . SHIPS FROM MULTIPLE LOCATIONS. book.
- Softcover
- Print on Demand
Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
- Softcover
- Print on Demand
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
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PAP. 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.
- Softcover
- Print on Demand
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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Condition: New. Print on Demand pp. 254.
- Softcover
- Print on Demand
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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Condition: New. PRINT ON DEMAND pp. 254.
- Softcover
- Print on Demand
Seller: THE SAINT BOOKSTORE, Southport, United KingdomTHE SAINT BOOKSTORE
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Paperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
- Softcover
- Print on Demand
Seller: moluna, Greven, Germanymoluna
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£ 53.56
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextThis book examines machine learning models including k-nearest neighbors, logistic regression, naive Bayes, random forests, and support vector machines. You will work through document classification, image…recognition, and oth.
- Softcover
- Print on Demand
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book examines machine learning models including k-nearest neighbors, logistic regression, naive Bayes, random forests, and support vector machines. You will work through document classification, image recognition, and other example…problems.
