** UPDATE: The videos for the course are now out!! Take a look at the fast.ai site for details: https://course.fast.ai/ **

We're back for round 2 of our ML workgroup and we will remain online for the duration of this course!!
Over the next few months we will work through the new version of the fast.ai course, "Practical Deep Learning For Coders v4, Part 1", this time using the latest version of the fast.ai api and the Fastbook.

We will be covering the remainder of lesson 6 (https://course.fast.ai/videos/?lesson=6) and part of lesson 7 (https://course.fast.ai/videos/?lesson=7)
1. https://github.com/fastai/fastbook/blob/master/08_collab.ipynb
2. https://github.com/fastai/fastbook/blob/master/09_tabular.ipynb

In 08_collab.ipynb, we will look at collaborative filtering and build these models from scratch. We will also learn about weight decay, embeddings, and interpreting various outputs of the model.

In 09_tabular.ipynb, we will be covering the tabular model and try to make predictions of supermarket sales. We will also build some decision trees and from there random forests.

The format has changed - we will provide a very brief overview of the key contents of the notebook and walk through the questions in a 30-40 min session.

Tentative Agenda:
18:45 - Social chat, introduce yourself, questions, etc
18:59 - Overview: Maria & Perusha
19:00 - 08_collab and 09_tabular: Mark and Maria
19:40 - Projects:
- TBA

Links for this lesson:
https://github.com/fastai/fastbook/blob/master/08_collab.ipynb
https://github.com/fastai/fastbook/blob/master/09_tabular.ipynb

Course Details:

Course content is here: https://course.fast.ai/
Fastbook is here: https://github.com/fastai/fastbook
Fastbook notebooks without the text (just code blocks) are here: https://github.com/fastai/fastbook/tree/master/clean

How to get the most out of the course:

- Commit time every week - the videos/notebooks take a lot of time to digest and work through.
- Suggest starting with 2-3 hours for the video. The videos are dense so you may want to stop it and make sure you understand as you go. Making notes in your copy of the fastbook may be useful for later review.
- Often 2-3 notebooks are covered in one video. Each notebook can take a lot of time to work through so allocate at least 1-2 hours per notebook
- If you are stuck ask questions on the slack channel or search the fast.ai forums for similar questions. The fast.ai community is vast so someone is bound to be able to help especially now with the general release of the course
- People are expected to have completed the material in their own time/pace before the event to be able to fully participate.
- We will space the online events 3-4 weeks apart to give people sufficient time to complete the assignments. It is likely that we will remain online until it is safe for everyone to re-emerge!