Over the past few months we worked through fast.ai's "Practical Deep Learning For Coders v3, Part 1": https://course.fast.ai/. This is our final lesson! Well done for staying with us!!
Join us for lesson 7:
Lesson 7 - Resnets, Densenets, GANs, RNNs
18:30 - 19:00 - Social chat, questions on the group/meetup
19:00 - 20:00 - Overview: Maria & Perusha
Review of notebooks:
Resnet and MNIST: Mark Oppenheim
Superes: Generative models for image restoration: Theo Carper
Human Numbers - RNNs: Kalidass Mookkaiah
20:00 - 21:00 PM - open discussion, Q&A
- Practical Deep Learning For Coders v3, Part 1": https://course.fast.ai/
- People are expected to watch the lesson video at home and work on the assignments before the event to be able to fully participate.
- We will space the face to face events 2-3 weeks apart to give people sufficient time to complete the assignments.
- There is a slack channel.
We are at the end of this course.
The new version of this course (v4) is out in July along with a new release of the fast.ai framework (v2). If you are just joining us, you may want to start on the new version in June or try to catch up with the live stream and current study groups via TWiML (https://twimlai.com/community/).
Some resources for v4 are below:
A book version of the new course: https://github.com/fastai/fastbook
The new framework (v2): https://github.com/fastai/fastai2
A starter notebook to install v2: https://colab.research.google.com/drive/1ao9E-yVfTt5TzTKmnjrVQqi5rphZMYFb