The material you find here is currently being produced to support the activities of the study group
Tarallucci, Vino e Machine Learning based in Verona, Italy.
Facebook: https://www.meetup.com/Tarallucci-Vino-Machine-Learning
Meetup: https://www.meetup.com/Tarallucci-Vino-Machine-Learning
Story https://medium.com/@cesaremontresor/fast-ai-notebooks-google-colab-ready-44a67be5c14b
Porting of fast.ai python notebooks classes for Google Colab platform.
Notebooks are divided in 2 folders to reflect the original structure of the course: dl1, dl2 Every notebook is also numbered in a progressive order from 1 to 14, where from 1 to 7 would be part 1 and 8-14 would be part 2.
The porting may be imperfect and some of the dependecies might be not needed, also, I've been porting ONLY the notebooks used in the actual videos.
Consider yourself encouraged to open an issue/pull-request and help me to perfect them.
For the notebook that use Kaggle datasets, it's required to perform the following steps, in order to be able to download them on-the-fly:
- Register an account on https://www.kaggle.com ( one-time )
- Verify your phone number ( one-time )
- Generate and Download a API Token from: My Account > API > Generate new token ( one-time )
- Accept the terms of the specific competition: Rules > "I understand and accept"
- Paste the content of kaggle.json in the notebook ( see instructions in the notebook )
We are currently at lesson 10 (part2, lesson 3), so there are some missing notebooks, they will be ported when the class will be prepared. However, as we will do it anyway, feel free to pop me a message to ask to add a missing notebook ^_^