Plans for week 42
Dear all, two short messages first during this hectic weekend with project 1 and the exercises for week 41.
1) You can hand in the exercises for week 41 with deadline Sunday 15 on Sunday the 22nd, and you can hand them in together with the exercises for week 42. You will get a score for both then. If you were busy with project 1 till late today, feel free to hand this in later.
2) If you need to adjust project 1, feel free to do so till tomorrow at the end of the working day, that is Monday october 16 at 6pm in the afternoon. We will not subtract points. We will start grading after that. GitHub/Gitlab have a time stamp. Thus, feel free to amend/correct if it got too hectic today!
Best wishes to you all with the project.
Else, the plans for this coming week are
Plan for week 42
Material for the active learning sessions on Tuesday and Wednesday
- Exercise on writing your own stochastic gradient and gradient descent codes. This exercise continues from the previous week but now with inclusion of automatic differentiation.
- Discussion of project 2
- See video on automatic differentiation from last yearLinks to an external site.
. This video will be updated before Tuesday.
Material for the lecture on Thursday October 12, 2023
- Building our own Feed-forward Neural Network and discussion of project 2
- Readings and Videos:
- These lecture notes
- Aurelien Geron's chapters 10-11Links to an external site.
- For a more in depth discussion on neural networks we recommend Goodfellow et al chapters 6 and 7.
- Neural Networks demystifiedLinks to an external site.
- Building Neural Networks from scratchLinks to an external site.
- Video on Neural NetworksLinks to an external site.
- Video on the back propagation algorithmLinks to an external site.
I also recommend Michael Nielsen's intuitive approach to the neural networks and the universal approximation theorem, see the slides at http://neuralnetworksanddeeplearning.com/chap4.htmlLinks to an external site..