siran / fastai_deeplearn_part1

Notes for Fastai Deep Learning Course - Part 1 v2

fast.ai

Deep Learning (Part 1 v2): Oct - Dec 2017

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About Me

Reshama Shaikh blog: https://reshamas.github.io
I am on Twitter: https://twitter.com/reshamas

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Course Links

• GitHub: fastai
• Discourse: part1-v2
• Discourse: part1-v2 beginner
• some fastai files

Helpful Resources

• Directory of fastai and DL terms
• Solving the Most Common Errors
• Fastai FAQs for Beginners
• 🔴 Resources (Blogs Written by fastai Fellows / Research Papers, etc)
  • Fastai Blog Posts (by Rachel Thomas & Jeremy Howard)

Platforms for Using fastai (GPU required)

• Paperspace setup
• AWS AMI GPU Setup
• Crestle
• Google Cloud GPU Setup for fastai
• Paperspace Docker Container
• Set up personal deep learning box (home computer)
• Microsoft Azure
• manual: bash script for setup
  • the CUDA drivers
  • Anaconda (special Python distribution)
  • Python libraries
  • fastai library
  • courses
  • data
• Other
  • FloydHub
  • Google Colaboratory

Technical Tools

• tmux on AWS
• Download data using Kaggle CLI
• Download data using Chrome and wget
• Jupyter Notebook Commands & Shortcuts
• How to Create a Keypair

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Course Info

Deep Learning Wiki

• http://forums.fast.ai/t/welcome-to-part-1-v2/5787
• http://forums.fast.ai/t/another-treat-early-access-to-intro-to-machine-learning-videos/6826
• Latest coursework
  • Version 2: Part 1 v2 (released Jan 2018)
  • Version 2: [Part 2 v2] (will be released ~ Jul 2018)
• Older coursework
  • Version 1: Part 1 v1
  • Version 1: Part 2 v1

Deep Learning Lesson Timelines

• http://forums.fast.ai/t/part-1-v2-complete-collection-of-video-timelines/11183

Deep Learning 1: My Lesson Notes

• Lesson 1
  • Lesson 1a: Course Intro
  • Lesson 1b: CNN and resnet Architecture
• Lesson 2: resnet34, resnext50
• Lesson 3: CNN Image Intro
• Lesson 4: Structured Neural Net Intro, Language RNN Intro, Collaborative Filtering Intro
• Lesson 5:
• Lesson 6:
• Lesson 7:

Intro to Machine Learning: My Lesson Notes

• Lesson 1: Random Forests Part 1
• Lesson 2: Random Forests Part 2
• Lesson 3: Preprocessing Data
• Lesson 4: RF Hyperparameters & Feature Importance
• [Lesson 5: ] (courses/ml1/)
• [Lesson 6: ] (courses/ml1/)
• [Lesson 7: ] (courses/ml1/)
• [Lesson 8: ] (courses/ml1/)
• [Lesson 9: ] (courses/ml1/)
• [Lesson 10: ] (courses/ml1/)
• [Lesson 11: ] (courses/ml1/)
• [Lesson 12: ] (courses/ml1/)