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020 _a9789355421982
040 _cIISER BPR
041 _aEng
082 _a006.31
_bGOR
_223rd
100 _aGéron, Aurélien
_9450
245 0 _aHands-on machine learning with scikit-learn, keras, and tensorflow :
_bConcepts, tools and techniques to build intelligent systems
250 _a3rd ed.
260 _aNavi Mumbai:
_bShroff Publishers & Distributors Pvt. Ltd,
_cc2023.
300 _axxv, 835p. :
_bill (col), (pbk). ;
_c23cm.
520 _aThrough 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 best-selling 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 Aurelien Geron 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 machine learning project end to end Explore several models, including support vector machines, decision trees, random forests, and ensemble methodsExploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, and transformers Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning Train neural nets using multiple GPUs and deploy them at scale using Google's Vertex AI Includes appendices and index.
650 _aComputer Sciences
_9451
650 _aSpecial Computer Methods
_9452
650 _aMachine Learning
_9453
942 _cBK
_2ddc
_07
942 _cBK
_2ddc
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947 _a3000
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