fast.ai

My personal notes from fast.ai course. These notes will continue to be updated and improved as I continue to review the course to "really" understand it.

• Deep Learning Part 1: 2018 Edition (v2): Oct - Dec 2017
• Deep Learning Part 1: 2019 Edition (v3): Oct - Dec 2018
• Deep Learning Part 2: 2017 Edition (v1): Feb - Apr 2017
• Deep Learning Part 2: 2018 Edition (v2): Mar - May 2018
• Machine Learning: 2017 Edition: Oct - Dec 2017

Main Course Links

• fastai library and Jupyter Notebook code
• Forum for part 1, v2
• Forum for part 1, v2 beginner
• Forum for part 2, v2 and alumni
• Forum for anything to do with deep learning that's not related to a fast.ai course
• Some fastai files, datasets and pre-trained models
• Forum for part 1, v3
• Forum for part 1, v3 advanced

Table of Contents

• Deep Learning Part 1: Practical Deep Learning for Coders
  • 2017 Edition (v1)
  • 2018 Edition (v2)
  • 2019 Edition (v3)
    • Lesson 1 - Image Recognition
    • Lesson 2 - Computer Vision: Deeper Applications
    • Lesson 3 - Multi-label, Segmentation, Image Regression, and More
    • Lesson 4 - NLP, Tabular, and Collaborative Filtering
    • Lesson 5 - Foundations of Neural Networks
    • Lesson 6 - Foundations of Convolutional Neural Networks
    • Lesson 7 - ResNets, U-Nets, GANs and RNNs
• Deep Learning Part 2: Cutting Edge Deep Learning for Coders
  • 2017 Edition (v1)
    • Lesson 8 - Artistic Style
    • Lesson 9 - Generative Models
    • Lesson 10 - Multi-modal & GANs
    • Lesson 11 - Memory Networks
    • Lesson 12 - Attentional Models
    • Lesson 13 - Neural Translation
    • Lesson 14 - Time Series & Segmentation
  • 2018 Edition (v2)
    • Lesson 8 - Object Detection
    • Lesson 9 - Single Shot Multibox Detector (SSD)
    • Lesson 10 - Transfer Learning for NLP and NLP Classification
    • Lesson 11 - Neural Translation; Multi-modal Learning
    • Lesson 12 - DarkNet; Generative Adversarial Networks (GANs)
    • Lesson 13 - Image Enhancement; Style Transfer; Data Ethics
    • Lesson 14 - Super Resolution; Image Segmentation with U-Net
• Machine Learning: Intro to Machine Learning for Coders
  • 2017 Edition
    • Lesson 1 - Introduction to Random Forests
    • Lesson 2 - Random Forest Deep Dive
    • Lesson 3 - Feature Engineering
    • Lesson 4 - Random Forest Interpretation
    • Lesson 5 - Train vs Test

Useful Resources

• fast.ai blog posts (by Jeremy Howard & Rachel Thomas)
• fast.ai FAQ for beginners
• fast.ai and deep learning key concepts
• Best practices

Tools for Deep Learning

• tmux
  • A terminal multiplexer
• Wget
  • A computer program that retrieves (downloads) content from web servers
• cURL
  • A command line tool for transferring data with URLs
• Secure Shell (SSH)
  • SSH client is used for securely connecting to remote computer
• SFTP (SSH File Transfer Protocol)
  • Securely transfer files between local computer and remote computer/server
• Jupyter Notebook
  • A web-based interactive computational environment for creating and sharing documents that contain live code, equations, visualizations and narrative text
• Kaggle API
  • Official Kaggle command line (CLI) tool to download Kaggle datasets