Learn to implement complex data structures and algorithms using Python

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Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow.

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With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field.

Build neural network models in text, vision and advanced analytics using PyTorch

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Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries

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Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras.

Skip the theory and get the most out of Tensorflow to build production-ready machine learning models

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A practical guide to mastering reinforcement learning algorithms using Keras

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Write modern natural language processing applications using deep learning algorithms and TensorFlow

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