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Loading... Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems (edition 2017)by Aurélien Géron (Author)
Work InformationHands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurélien Géron
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Sign up for LibraryThing to find out whether you'll like this book. No current Talk conversations about this book. A thorough yet engaging introduction to machine learning techniques and ideas using the popular scikit-learn python library. Well worth reading through for a solid grounding .in basic strategiies and techniques. ( ) no reviews | add a review
Through a recent series of 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 bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aur©?lien G©?ron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started. Use Scikit-learn to track an example ML project end to end; Explore several models, including support vector machines, decision trees, random forests, and ensemble methods; Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection; Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers; Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning. No library descriptions found. |
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Google Books — Loading... GenresMelvil Decimal System (DDC)006.31Information Computer Science; Knowledge and Systems Special Topics Artificial Intelligence Machine LearningLC ClassificationRatingAverage:
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