Deep Learning Resources

Neural Networks and Deep Learning Model Zoo

A collection of standalone TensorFlow models in Jupyter Notebooks

Python 3.6 TensorFlow

Classifiers

Metric Learning

Autoencoders

General Adversarial Networks

Other






Free Chapters from Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python

  • Introduction

  • The Perceptron [Code Notebook]

  • Optimizing Cost Functions with Gradient Descent

  • Logistic Regression and Softmax Regression

  • From Softmax Regression to Multi-layer Perceptrons

  • Cross Validation and Performance Metrics

  • Regularization in Neural Networks

  • Learning Rates and Weight Initialization

  • Convolutional Neural Networks

  • Recurrent Neural Networks

  • Echostate Networks

  • Autoencoders

  • General Adverserial Neural Networks

  • Deep Generative Models

  • Reinforcement Learning

  • Appendix A: Mathematical Notation [PDF] [EPUB]

  • Appendix B: Algebra Basics [PDF] [EPUB]

  • Appendix C: Linear Algebra Essentials

  • Appendix D: Calculus and Differentiation Primer [PDF] [EPUB]

  • Appendix E: Python Setup

  • Appendix F: Introduction to NumPy [PDF] [EPUB] [Code Notebook]

  • Appendix G: TensorFlow Basics [PDF] [EPUB] [Code Notebook]

  • Appendix H: Cloud Computing [PDF] [EPUB]