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Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow - Concepts, Tools, and Techniques to Build Intelligent Systems (Paperback, 2nd New edition)
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Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow - Concepts, Tools, and Techniques to Build Intelligent Systems (Paperback, 2nd New edition)
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Through 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 TensorFlow-author Aurelien Geron 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 nets Use Scikit-Learn to track an example machine-learning
project end-to-end Explore several training models, including
support vector machines, decision trees, random forests, and
ensemble methods Use the TensorFlow library to build and train
neural nets Dive into neural net architectures, including
convolutional nets, recurrent nets, and deep reinforcement learning
Learn techniques for training and scaling deep neural nets
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