Watched 2nd lecture on Deployment and 3rd lecture on Neural net foundations
Skipped the trying out deployment myself since I am proficient in deploying code. Instead I spent that time playing with the MNIST dataset in preparing for the 4th video lecture. The Chap 4 of fastbook goes into detail about the neural network so using the dataset in basic ways to get a good idea.
Learned about:
- Image transformations
- Data augmentation
- Loss functions & searching for parameters to minimise loss
- Rectified linear functions
- Learning rate