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fundamentals deep learning designing next generation machine

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Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms Author: Nikhil Buduma(2017) Publication Date: 2017-06-29 - ISBN-13: 9781491925614 - 304 pages - True PDF - English With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research that is paving the way for modern machine learning. This book uses exposition and examples to help you understand major concepts in this complicated field. Large companies such as Google, Microsoft, andhave taken notice, and are actively growing in-house deep learning teams. For the rest of us however, deep learning is still a pretty complex and difficult subject to grasp. If you have a basic understanding of what machine learning is, have familiarity with the Python programming language, and have some mathematical background with calculus, this book will help you get started. Table of Contents Chapter 1. The Neural Network Chapter 2. Training Feed-Forward Neural Networks Chapter 3. Implementing Neural Networks in TensorFlow Chapter 4. Beyond Gradient Descent Chapter 5. Convolutional Neural Networks Chapter 6. Embedding and Representation Learning Chapter 7. Models for Sequence Analysis Chapter 8. Memory Augmented Neural Networks Chapter 9. Deep Reinforcement Learning

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fundamentals deep learning designing next generation machine

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