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OReilly Fundamentals of Deep Learning 1491925612 pdf

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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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