There were several cool things at the FastAI deep learning course. Many of the ideas are worth checking out and digging deeper.
A few thoughts:
- One of the easy to copy ideas is the fastai/cups. I am going to copy that right away.
- It is amazing how many uses they found for Jupyter notebooks. I have known it as a great teaching tool, but the idea of writing a book or creating a blog post blows my mind.
- I got some cool references (books) to teaching techniques. Can’t wait to learn them.
- FastAI is built on top of PyTorch
- The mouse click image generator is cool
- The slides are in Jupyter Note books using a JN extension called REST #todo: Check out REST
- There are several notebook servers including the one from Kaggle
- Jerome prefers functional style of Python programming (time to revisit sicpy)
- JN as a blogging tool (fastpages). Need to checkit out (perhaps for pyskills)
- The diagrams on how ML works (attributed to Arthur Samuel) are a clever hack using GraphViz and JN). Need to check it ou.
- The entire course is on github. So I can go there and fill up these notes
- Tabular Analysis caught my attention. There were many applications including a whole set of NLP Tasks
- Data blocks,
- Data loaders
- Learners (cobines models and data)