This book will be a journey for beginners who want to step into the world of deep learning and artificial intelligence. It will thoughtfully take you through the training and implementation of various neural network architectures using the Python ecosystem. You will master each neural network architecture while understanding its working mechanism.
Contents
Hands-on neural networks: learn how to build and train your first neural network model using Python -- Dedication -- Contributors -- Table of Contents -- Preface -- Section 1: Getting Started -- Chapter 1: Getting Started with Supervised Learning -- Chapter 2: Neural Network Fundamentals -- Section 2: Deep Learning Applications -- Chapter 3: Convolutional Neural Networks for Image Processing -- Chapter 4: Exploiting Text Embedding -- Chapter 5: Working with RNNs -- Chapter 6: Reusing Neural Networks with Transfer Learning -- Section 3: Advanced Applications -- Chapter 7: Working with Generative Algorithms -- Chapter 8: Implementing Autoencoders -- Chapter 9: Deep Belief Networks -- Chapter 10: Reinforcement Learning -- Chapter 11: Whats Next? -- Other Books You May Enjoy -- Index.
Local Note
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