Dive into Deep Learning

Immerse yourself in Dive into Deep Learning, an engaging and accessible resource. Tailored for engineers, scientists, and students, it strikes a perfect balance between simplicity and technical rigor. You don’t need prior machine learning expertise; every concept is introduced anew. The appendix offers a math refresher, while practical runnable code instances foster intuitive understanding. Experience deep learning’s potential firsthand as you engage with this reader-friendly guide.

Table of Contents

• Introduction
• Preliminaries
• Linear Neural Networks for Regression
• Linear Neural Networks for Classification
• Multilayer Perceptrons
• Builders’ Guide
• Convolutional Neural Networks
• Modern Convolutional Neural Networks
• Recurrent Neural Networks
• Modern Recurrent Neural Networks
• Attention Mechanisms and Transformers
• Optimization Algorithms
• Computational Performance
• Computer Vision
• Natural Language Processing: Pretraining
• Natural Language Processing: Applications
• Reinforcement Learning
• Gaussian Processes
• Hyperparameter Optimization
• Generative Adversarial Networks
• Recommender Systems

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