Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

Description: INFORMATIONS AND SHIPPINGShippingAfter the book shipped out, you will receive your order in a week as a maximumUsually ships within 1 to 4 weeksFastest delivery: 1 to 2 weeks maximumFeedbackWe appreciate your positive feedback.Please email us before leaving negative and neutral feedback, we will try our best to solve the issue.Your satisfaction is our first priority.Contact UsIf you have any problems, we are very glad to help you. Please contact us anytime for any question via eBay message we will reply you within 10 minutes to 12 hours.+ THANK YOU FOR YOUR CONFIDENCE +PRODUCT DETAILSBook Title: Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems 2nd EditionPaperback: 856 pagesPublisher: O'Reilly Media; 2nd edition (October 15, 2019)Language: EnglishProduct Dimensions: 7 x 1.2 x 9.2 inchesShipping Weight: 2.8 poundsABOUT THE BOOKThrough a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and Tensor Flow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.Explore the machine learning landscape particularly neural netsUse Scikit-Learn to track an example machine-learning project end-to-endExplore several training models, including support vector machines, decision trees, random forests, and ensemble methodsUse the Tensor Flow library to build and train neural netsDive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learningLearn techniques for training and scaling deep neural nets.

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Location: Springfield Gardens, New York

End Time: 2024-10-07T18:46:49.000Z

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