Edité par Packt Publishing, Limited, 2020
ISBN 10 : 1838826041 ISBN 13 : 9781838826048
Langue: anglais
Vendeur : Better World Books, Mishawaka, IN, Etats-Unis
EUR 7,64
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierEtat : Very Good. Used book that is in excellent condition. May show signs of wear or have minor defects.
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
EUR 43,10
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New. In.
Edité par Packt Publishing 2020-07, 2020
ISBN 10 : 1838826041 ISBN 13 : 9781838826048
Langue: anglais
Vendeur : Chiron Media, Wallingford, Royaume-Uni
EUR 38,07
Autre deviseQuantité disponible : 10 disponible(s)
Ajouter au panierPF. Etat : New.
Vendeur : California Books, Miami, FL, Etats-Unis
EUR 43,15
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New.
Edité par Packt Publishing 7/24/2020, 2020
ISBN 10 : 1838826041 ISBN 13 : 9781838826048
Langue: anglais
Vendeur : BargainBookStores, Grand Rapids, MI, Etats-Unis
EUR 42,39
Autre deviseQuantité disponible : 5 disponible(s)
Ajouter au panierPaperback or Softback. Etat : New. Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits: A practical guide to implementing supervised and unsupervised machine lear 1.45. Book.
Vendeur : moluna, Greven, Allemagne
EUR 48,76
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New. This book covers the theory and practice of building data-driven solutions. Includes the end-to-end process, using supervised and unsupervised algorithms. With each algorithm, you will learn the data acquisition and data engineering methods, the apt metrics.
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
EUR 38,36
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New.
Vendeur : Toscana Books, AUSTIN, TX, Etats-Unis
EUR 96,94
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panier
Vendeur : Best Price, Torrance, CA, Etats-Unis
EUR 34,58
Autre deviseQuantité disponible : 2 disponible(s)
Ajouter au panierEtat : New. SUPER FAST SHIPPING.
Edité par Packt Publishing Limited, 2020
ISBN 10 : 1838826041 ISBN 13 : 9781838826048
Langue: anglais
Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
EUR 48,98
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierPAP. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Edité par Packt Publishing Limited, 2020
ISBN 10 : 1838826041 ISBN 13 : 9781838826048
Langue: anglais
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
EUR 47,55
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierPaperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 526.
Edité par Packt Publishing, Limited, 2020
ISBN 10 : 1838826041 ISBN 13 : 9781838826048
Langue: anglais
Vendeur : Majestic Books, Hounslow, Royaume-Uni
EUR 47,71
Autre deviseQuantité disponible : 4 disponible(s)
Ajouter au panierEtat : New. Print on Demand pp. 384.
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
EUR 60,46
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierTaschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Integrate scikit-learn with various tools such as NumPy, pandas, imbalanced-learn, and scikit-surprise and use it to solve real-world machine learning problemsKey FeaturesDelve into machine learning with this comprehensive guide to scikit-learn and scientific PythonMaster the art of data-driven problem-solving with hands-on examplesFoster your theoretical and practical knowledge of supervised and unsupervised machine learning algorithmsBook DescriptionMachine learning is applied everywhere, from business to research and academia, while scikit-learn is a versatile library that is popular among machine learning practitioners. This book serves as a practical guide for anyone looking to provide hands-on machine learning solutions with scikit-learn and Python toolkits.The book begins with an explanation of machine learning concepts and fundamentals, and strikes a balance between theoretical concepts and their applications. Each chapter covers a different set of algorithms, and shows you how to use them to solve real-life problems. You'll also learn about various key supervised and unsupervised machine learning algorithms using practical examples. Whether it is an instance-based learning algorithm, Bayesian estimation, a deep neural network, a tree-based ensemble, or a recommendation system, you'll gain a thorough understanding of its theory and learn when to apply it. As you advance, you'll learn how to deal with unlabeled data and when to use different clustering and anomaly detection algorithms.By the end of this machine learning book, you'll have learned how to take a data-driven approach to provide end-to-end machine learning solutions. You'll also have discovered how to formulate the problem at hand, prepare required data, and evaluate and deploy models in production.What you will learnUnderstand when to use supervised, unsupervised, or reinforcement learning algorithmsFind out how to collect and prepare your data for machine learning tasksTackle imbalanced data and optimize your algorithm for a bias or variance tradeoffApply supervised and unsupervised algorithms to overcome various machine learning challengesEmploy best practices for tuning your algorithm's hyper parametersDiscover how to use neural networks for classification and regressionBuild, evaluate, and deploy your machine learning solutions to productionWho this book is forThis book is for data scientists, machine learning practitioners, and anyone who wants to learn how machine learning algorithms work and to build different machine learning models using the Python ecosystem. The book will help you take your knowledge of machine learning to the next level by grasping its ins and outs and tailoring it to your needs. Working knowledge of Python and a basic understanding of underlying mathematical and statistical concepts is required.