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Generative Deep Learning
Author: David Foster
This book provides a practical guide to creating generative models using TensorFlow and Keras, covering various architectures like VAEs, GANs, and Transformers.
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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
Author: Aurelien Geron
A comprehensive resource that covers a wide range of machine learning techniques, including deep learning and NLP, with practical examples in Python.
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Natural Language Processing with Python
Authors: Steven Bird, Ewan Klein, and Edward Loper
This book offers an introduction to NLP using Python, guiding readers through building working NLP tools.
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Artificial Intelligence: A Modern Approach
Authors: Stuart Russell and Peter Norvig
A widely-used textbook that provides a comprehensive introduction to the theory and practice of AI, including machine learning and NLP.
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Deep Learning
Authors: Ian Goodfellow, Yoshua Bengio, and Aaron Courville
This book offers an in-depth exploration of deep learning techniques, essential for understanding advanced machine learning and generative models.
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Generative AI with Python and TensorFlow 2
Authors: Joseph Babcock and Raghav Bali
This book guides you through building generative models, including VAEs and GANs, using Python and TensorFlow 2.
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Introduction to Natural Language Processing
Author: Jacob Eisenstein
An accessible introduction to NLP, covering both the theoretical foundations and practical applications.
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The Hundred-Page Machine Learning Book
Author: Andriy Burkov
A concise yet comprehensive guide to machine learning concepts, suitable for both beginners and experienced practitioners.
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Natural Language Processing with PyTorch
Authors: Delip Rao and Brian McMahan
This book provides practical guidance on building NLP applications using the PyTorch library.
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Generative AI with LangChain
Author: Ben Auffarth
A comprehensive guide to building large language model applications using the LangChain framework.