Tim Holtz

Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and dee

Description: Machine Learning with PyTorch and Scikit-Learn by Sebastian Raschka, Yuxi Liu, Vahid Mirjalili, Dmytro Dzhulgakov Estimated delivery 3-12 business days Format Paperback Condition Brand New Description Packed with clear explanations, visualizations, and working examples, the book covers essential machine learning techniques in depth, along with two cutting-edge machine learning techniques: transformers and graph neural networks. Publisher Description This book of the bestselling and widely acclaimed Python Machine Learning series is a comprehensive guide to machine and deep learning using PyTorch s simple to code framework.Purchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesLearn applied machine learning with a solid foundation in theoryClear, intuitive explanations take you deep into the theory and practice of Python machine learningFully updated and expanded to cover PyTorch, transformers, XGBoost, graph neural networks, and best practicesBook DescriptionMachine Learning with PyTorch and Scikit-Learn is a comprehensive guide to machine learning and deep learning with PyTorch. It acts as both a step-by-step tutorial and a reference youll keep coming back to as you build your machine learning systems.Packed with clear explanations, visualizations, and examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, we teach the principles allowing you to build models and applications for yourself.Why PyTorch?PyTorch is the Pythonic way to learn machine learning, making it easier to learn and simpler to code with. This book explains the essential parts of PyTorch and how to create models using popular libraries, such as PyTorch Lightning and PyTorch Geometric.You will also learn about generative adversarial networks (GANs) for generating new data and training intelligent agents with reinforcement learning. Finally, this new edition is expanded to cover the latest trends in deep learning, including graph neural networks and large-scale transformers used for natural language processing (NLP).This PyTorch book is your companion to machine learning with Python, whether youre a Python developer new to machine learning or want to deepen your knowledge of the latest developments.What you will learnExplore frameworks, models, and techniques for machines to learn from dataUse scikit-learn for machine learning and PyTorch for deep learningTrain machine learning classifiers on images, text, and moreBuild and train neural networks, transformers, and boosting algorithmsDiscover best practices for evaluating and tuning modelsPredict continuous target outcomes using regression analysisDig deeper into textual and social media data using sentiment analysisWho this book is forIf you have a good grasp of Python basics and want to start learning about machine learning and deep learning, then this is the book for you. This is an essential resource written for developers and data scientists who want to create practical machine learning and deep learning applications using scikit-learn and PyTorch.Before you get started with this book, youll need a good understanding of calculus, as well as linear algebra. Author Biography Sebastian Raschka is an Assistant Professor of Statistics at the University of Wisconsin-Madison focusing on machine learning and deep learning research. As Lead AI Educator at Grid AI, Sebastian plans to continue following his passion for helping people get into machine learning and artificial intelligence. Yuxi (Hayden) Liu was a Machine Learning Software Engineer at Google. With a wealth of experience from his tenure as a machine learning scientist, he has applied his expertise across data-driven domains and applied his ML expertise in computational advertising, cybersecurity, and information retrieval.He is the author of a series of influential machine learning books and an education enthusiast. His debut book, also the first edition of Python Machine Learning by Example, ranked the #1 bestseller in Amazon and has been translated into many different languages. Vahid Mirjalili is a deep learning researcher focusing on CV applications. Vahid received a Ph.D. degree in both Mechanical Engineering and Computer Science from Michigan State University. Details ISBN 1801819319 ISBN-13 9781801819312 Title Machine Learning with PyTorch and Scikit-Learn Author Sebastian Raschka, Yuxi Liu, Vahid Mirjalili, Dmytro Dzhulgakov Format Paperback Year 2022 Pages 774 Publisher Packt Publishing Limited GE_Item_ID:134305484; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys

Price: 62.74 USD

Location: Fairfield, Ohio

End Time: 2024-10-04T03:41:23.000Z

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Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and dee

Item Specifics

Restocking Fee: No

Return shipping will be paid by: Buyer

All returns accepted: Returns Accepted

Item must be returned within: 30 Days

Refund will be given as: Money Back

ISBN-13: 9781801819312

Book Title: Machine Learning with PyTorch and Scikit-Learn

Publisher: Packt Publishing, The Limited

Publication Year: 2022

Subject: Expert Systems, Neural Networks, General, Speech & Audio Processing

Number of Pages: 774 Pages

Publication Name: Machine Learning with Pytorch and Scikit-Learn : Develop Machine Learning and Deep Learning Models with Python

Language: English

Type: Textbook

Author: Yuxi (Hayden) Liu, Vahid Mirjalili, Dmytro Dzhulgakov, Sebastian Raschka

Subject Area: Computers, Science

Format: Trade Paperback

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