# fast.ai

*My personal notes from* [*fast.ai course*](http://www.fast.ai/)*. 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)**](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-1-practical-deep-learning-for-coders/2018-edition): Oct - Dec 2017
* [**Deep Learning Part 1: 2019 Edition (v3)**](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-1-practical-deep-learning-for-coders/2019-edition): Oct - Dec 2018
* [**Deep Learning Part 2: 2017 Edition (v1)**](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-2-cutting-edge-deep-learning-for-coders/2017-edition): Feb - Apr 2017
* [**Deep Learning Part 2: 2018 Edition (v2)**](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-2-cutting-edge-deep-learning-for-coders/2018-edition): Mar - May 2018
* [**Machine Learning: 2017 Edition**](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/machine-learning-intro-to-machine-learning-for-coders/2017-edition): Oct - Dec 2017

## Main Course Links

* [fastai library and Jupyter Notebook code](https://github.com/fastai/fastai)
* [Forum for part 1, v2](http://forums.fast.ai/c/part1-v2)
* [Forum for part 1, v2 beginner](http://forums.fast.ai/c/part1v2-beg)
* [Forum for part 2, v2 and alumni](http://forums.fast.ai/c/part2-v2)
* [Forum for anything to do with deep learning that's not related to a fast.ai course](http://forums.fast.ai/c/deep-learning)
* [Some fastai files, datasets and pre-trained models](http://files.fast.ai/)
* [Forum for part 1, v3](https://forums.fast.ai/c/part1-v3)
* [Forum for part 1, v3 advanced](https://forums.fast.ai/c/part1-v3/part1-v3-adv)

## Table of Contents

* Deep Learning Part 1: Practical Deep Learning for Coders
  * 2017 Edition (v1)
  * [2018 Edition (v2)](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-1-practical-deep-learning-for-coders/2018-edition)
  * [2019 Edition (v3)](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-1-practical-deep-learning-for-coders/2019-edition)
    * [Lesson 1 - Image Recognition](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-1-practical-deep-learning-for-coders/2019-edition/lesson-1-image-recognition)
    * [Lesson 2 - Computer Vision: Deeper Applications](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-1-practical-deep-learning-for-coders/2019-edition/lesson-2-deeper-dive-into-cv)
    * [Lesson 3 - Multi-label, Segmentation, Image Regression, and More](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-1-practical-deep-learning-for-coders/2019-edition/lesson-3-multilabel-segmentation)
    * [Lesson 4 - NLP, Tabular, and Collaborative Filtering](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-1-practical-deep-learning-for-coders/2019-edition/lesson-4-nlp-tabular-collab)
    * [Lesson 5 - Foundations of Neural Networks](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-1-practical-deep-learning-for-coders/2019-edition/lesson-5-foundations-neural-nets)
    * [Lesson 6 - Foundations of Convolutional Neural Networks](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-1-practical-deep-learning-for-coders/2019-edition/lesson-6-foundations-convolutional-neural-nets)
    * [Lesson 7 - ResNets, U-Nets, GANs and RNNs](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-1-practical-deep-learning-for-coders/2019-edition/lesson-7-resnet-unet-gan-rnn)
* Deep Learning Part 2: Cutting Edge Deep Learning for Coders
  * [2017 Edition (v1)](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-2-cutting-edge-deep-learning-for-coders/2017-edition)
    * [Lesson 8 - Artistic Style](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-2-cutting-edge-deep-learning-for-coders/2017-edition/lesson-8-artistic-style)
    * [Lesson 9 - Generative Models](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-2-cutting-edge-deep-learning-for-coders/2017-edition/lesson-9-generative-models)
    * [Lesson 10 - Multi-modal & GANs](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-2-cutting-edge-deep-learning-for-coders/2017-edition/lesson-10-multi-modal-and-gans)
    * [Lesson 11 - Memory Networks](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-2-cutting-edge-deep-learning-for-coders/2017-edition/lesson-11-memory-networks)
    * [Lesson 12 - Attentional Models](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-2-cutting-edge-deep-learning-for-coders/2017-edition/lesson-12-attentional-models)
    * [Lesson 13 - Neural Translation](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-2-cutting-edge-deep-learning-for-coders/2017-edition/lesson-13-neural-translation)
    * [Lesson 14 - Time Series & Segmentation](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-2-cutting-edge-deep-learning-for-coders/2017-edition/lesson-14-time-series-and-segmentation)
  * [2018 Edition (v2)](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-2-cutting-edge-deep-learning-for-coders/2018-edition)
    * [Lesson 8 - Object Detection](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-2-cutting-edge-deep-learning-for-coders/2018-edition/lesson-8-object-detection)
    * [Lesson 9 - Single Shot Multibox Detector (SSD)](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-2-cutting-edge-deep-learning-for-coders/2018-edition/lesson-9-multi-object-detection)
    * [Lesson 10 - Transfer Learning for NLP and NLP Classification](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-2-cutting-edge-deep-learning-for-coders/2018-edition/lesson-10-transfer-learning-nlp)
    * [Lesson 11 - Neural Translation; Multi-modal Learning](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-2-cutting-edge-deep-learning-for-coders/2018-edition/lesson-11-neural-translation)
    * [Lesson 12 - DarkNet; Generative Adversarial Networks (GANs)](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-2-cutting-edge-deep-learning-for-coders/2018-edition/lesson-12-gan)
    * [Lesson 13 - Image Enhancement; Style Transfer; Data Ethics](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-2-cutting-edge-deep-learning-for-coders/2018-edition/lesson-13-image-enhancement)
    * [Lesson 14 - Super Resolution; Image Segmentation with U-Net](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/deep-learning-part-2-cutting-edge-deep-learning-for-coders/2018-edition/lesson-14-image-segmentation)
* Machine Learning: Intro to Machine Learning for Coders
  * [2017 Edition](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/machine-learning-intro-to-machine-learning-for-coders/2017-edition)
    * [Lesson 1 - Introduction to Random Forests](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/machine-learning-intro-to-machine-learning-for-coders/2017-edition/lesson-1-intro-random-forests)
    * [Lesson 2 - Random Forest Deep Dive](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/machine-learning-intro-to-machine-learning-for-coders/2017-edition/lesson-2-random-forest-deep-dive)
    * [Lesson 3 - Feature Engineering](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/machine-learning-intro-to-machine-learning-for-coders/2017-edition/lesson-3-feature-engineering)
    * [Lesson 4 - Random Forest Interpretation](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/machine-learning-intro-to-machine-learning-for-coders/2017-edition/lesson-4-random-forest-interpretation)
    * [Lesson 5 - Train vs Test](https://cedrickchee.gitbook.io/knowledge/courses/fast.ai/machine-learning-intro-to-machine-learning-for-coders/2017-edition/lesson-5-train-vs-test)
    * [Lesson 6 - What is Machine Learning and Why Do We Use It](https://github.com/cedrickchee/knowledge/tree/83461b2e59b1b5d32305e15d9658554b36f630d5/courses/fast.ai/machine-learning/2017-edition/lesson-6-what-is-ml-and-why.md)
    * [Lesson 7 - Decision Trees Ensemble](https://github.com/cedrickchee/knowledge/tree/83461b2e59b1b5d32305e15d9658554b36f630d5/courses/fast.ai/machine-learning/2017-edition/lesson-7-decision-trees-ensemble.md)
    * [Lesson 8 - Basic Neural Networks](https://github.com/cedrickchee/knowledge/tree/83461b2e59b1b5d32305e15d9658554b36f630d5/courses/fast.ai/machine-learning/2017-edition/lesson-8-basic-neaural-nets.md)
    * [Lesson 9 - SGD; Neural Network Training; Broadcasting](https://github.com/cedrickchee/knowledge/tree/83461b2e59b1b5d32305e15d9658554b36f630d5/courses/fast.ai/machine-learning/2017-edition/lesson-9-broadcasting-matrix-multiplication.md)
    * [Lesson 10 - Logistic Regression; NLP; Naive Bayes](https://github.com/cedrickchee/knowledge/tree/83461b2e59b1b5d32305e15d9658554b36f630d5/courses/fast.ai/machine-learning/2017-edition/lesson-10-regression-nlp-naive-bayes.md)
    * [Lesson 11 - Structured and Time-Series Data](https://github.com/cedrickchee/knowledge/tree/83461b2e59b1b5d32305e15d9658554b36f630d5/courses/fast.ai/machine-learning/2017-edition/lesson-11-structured-time-series-data.md)
    * [Lesson 12 - Entity Embeddings; Data Science and Ethics](https://github.com/cedrickchee/knowledge/tree/83461b2e59b1b5d32305e15d9658554b36f630d5/courses/fast.ai/machine-learning/2017-edition/lesson-12-embeddings-datascience-ethics.md)

## Useful Resources

* [fast.ai blog posts (by Jeremy Howard & Rachel Thomas)](http://www.fast.ai/topics/)
* fast.ai FAQ for beginners
* fast.ai and deep learning key concepts
* [Best practices](http://forums.fast.ai/t/30-best-practices/12344)

## Tools for Deep Learning

* [tmux](https://github.com/tmux/tmux/wiki)
  * A terminal multiplexer
* [Wget](https://en.wikipedia.org/wiki/Wget)
  * A computer program that retrieves (downloads) content from web servers
* [cURL](https://curl.haxx.se/)
  * A command line tool for transferring data with URLs
* [Secure Shell (SSH)](https://en.wikipedia.org/wiki/Secure_Shell)
  * SSH client is used for securely connecting to remote computer
* [SFTP (SSH File Transfer Protocol)](https://en.wikipedia.org/wiki/SSH_File_Transfer_Protocol)
  * Securely transfer files between local computer and remote computer/server
* [Jupyter Notebook](http://jupyter.org/)
  * A web-based interactive computational environment for creating and sharing documents that contain live code, equations, visualizations and narrative text
* [Kaggle API](https://github.com/Kaggle/kaggle-api)
  * Official Kaggle command line (CLI) tool to download Kaggle datasets