Session Notebook links:
- Lecture 1: https://jovian.ml/aakashns/fastai2-chapter-1
- Lecture 2: Bears Training | Repo for Binder Deployment
- Lecture 3: https://jovian.ml/aakashns/fastai2-chapter-4
- Lecture 4: https://docs.google.com/presentation/d/1chVau7EXuSTGSr0OtFIcNpXkIL830XT7lG9ggS_5R1E/edit?usp=sharing
To mark the halfway point in the course, we’ll be reviewing all the material for Chapters 1-4. This is a great opportunity to join the live course as a newcomer or to catch up if you’ve missed any of the previous lectures. Please feel free to invite your friends and colleagues to join this study group.
The following topics will be explained via Juptyer notebooks & live coding:
- Chapter 1: Intro to Deep Learning & FastAI
- Chapter 2: Creating Web apps with Deep Learning Models
- Chapter 3: MNIST Image Classification in Depth
- Chapter 4: Data Ethics
After the review session, you’ll be able to build state-of-the-art Deep learning models, create simple web apps to try out & share your models, get an understanding of the inner workings of how deep learning models are trained in PyTorch & FastAI, and become aware of the ethical challenges involved in using AI for real-world applications.
This review session will also give you the perfect foundation to follow along live for the lectures 5-8, which will be streamed over the next 4 weeks, on Wednesday, from 7-9 pm.
- FastAI book: https://github.com/fastai/fastbook
- DSNet study group: https://jovian.ml/forum/c/dsnet-fastai-study-group
- FastAI library docs: https://dev.fast.ai/
How to Invite Friends/Colleagues
This public meetup link contains all the details: https://www.meetup.com/dsnet-blr/events/269928938/