From 63acbc3e9cb40f85f7946ae3264a4075ed006e74 Mon Sep 17 00:00:00 2001 From: Marc Lelarge Date: Tue, 20 Jun 2023 10:40:12 +0200 Subject: [PATCH] fin course --- index.md | 21 ++++++++++++++++++++- 1 file changed, 20 insertions(+), 1 deletion(-) diff --git a/index.md b/index.md index e098b33..7d26b09 100644 --- a/index.md +++ b/index.md @@ -81,6 +81,7 @@ Be sure to build your own classifier with more dogs and cats in the practicals. - [Module 8c - Word2vec](https://dataflowr.github.io/website/modules/8c-word2vec/) and build your own word embedding [08\_Word2vec\_pytorch\_empty.ipynb](https://github.com/dataflowr/notebooks/blob/master/Module8/08_Word2vec_pytorch_empty.ipynb) - [Module 16 - Batchnorm](https://dataflowr.github.io/website/modules/16-batchnorm/) and check your understanding with [16\_simple\_batchnorm\_eval.ipynb](https://github.com/dataflowr/notebooks/blob/master/Module16/16_simple_batchnorm_eval.ipynb) and more [16\_batchnorm\_simple.ipynb](https://github.com/dataflowr/notebooks/blob/master/Module16/16_batchnorm_simple.ipynb) - [Module 17 - Resnets](https://dataflowr.github.io/website/modules/17-resnets/) +- start of [Homework 2: Class Activation Map and adversarial examples](https://dataflowr.github.io/website/homework/2-CAM-adversarial/) ~~~
Things to remember @@ -97,12 +98,30 @@ Be sure to build your own classifier with more dogs and cats in the practicals. - [Module 9a: Autoencoders](https://dataflowr.github.io/website/modules/9a-autoencoders/) and code your noisy autoencoder [09\_AE\_NoisyAE.ipynb](https://github.com/dataflowr/notebooks/blob/master/Module9/09_AE_NoisyAE.ipynb) - [Module 10: Generative Adversarial Networks]() and code your GAN, Conditional GAN and InfoGAN [10\_GAN\_double\_moon.ipynb](https://github.com/dataflowr/notebooks/blob/master/Module10/10_GAN_double_moon.ipynb) - [Module 13: Siamese Networks and Representation Learning](https://dataflowr.github.io/website/modules/13-siamese/) +- start of [Homework 3: VAE for MNIST clustering and generation](https://dataflowr.github.io/website/homework/3-VAE/) ### :sunflower: Session 6 - [Module 11a - Recurrent Neural Networks theory](https://dataflowr.github.io/website/modules/11a-recurrent-neural-networks-theory/) - [Module 11b - Recurrent Neural Networks practice](https://dataflowr.github.io/website/modules/11b-recurrent-neural-networks-practice/) and predict engine failure with [11\_predicitions\_RNN\_empty.ipynb](https://github.com/dataflowr/notebooks/blob/master/Module11/11_predicitions_RNN_empty.ipynb) - [Module 11c - Batches with sequences in Pytorch](https://dataflowr.github.io/website/modules/11c-batches-with-sequences/) + ### :sunflower: Session 7 -TBA +- [Module 12 - Attention and Transformers](https://dataflowr.github.io/website/modules/12-attention/) +- Correcting the PyTorch tutorial on attention in seq2seq: [12\_seq2seq\_attention.ipynb](https://github.com/dataflowr/notebooks/blob/master/Module12/12_seq2seq_attention.ipynb) +- Build your own microGPT: [GPT\_hist.ipynb](https://github.com/dataflowr/notebooks/blob/master/Module12/GPT_hist.ipynb) + +### :sunflower: Session 8 +- [Module 9b - UNets](https://dataflowr.github.io/website/modules/9b-unet/) +- [Module 9c - Flows](https://dataflowr.github.io/website/modules/9c-flows/) +- Build your own Real NVP: [Normalizing\_flows\_empty.ipynb](https://github.com/dataflowr/notebooks/blob/master/Module9/Normalizing_flows_empty.ipynb) +### :sunflower: Session 9 +- [Module 18a - Denoising Diffusion Probabilistic Models](https://dataflowr.github.io/website/modules/18a-diffusion/) +- Train your own DDPM on MNIST: [ddpm\_nano\_empty.ipynb](https://github.com/dataflowr/notebooks/blob/master/Module18/ddpm_nano_empty.ipynb) +- Finetuning on CIFAR10: [ddpm\_micro\_sol.ipynb](https://github.com/dataflowr/notebooks/blob/master/Module18/ddpm_micro_sol.ipynb) + +For more updates: [![Twitter URL](https://img.shields.io/twitter/url/https/twitter.com/marc_lelarge.svg?style=social&label=Follow%20%40marc_lelarge)](https://twitter.com/marc_lelarge) + +and check the +# [GitHub repository: dataflowr/notebooks](https://github.com/dataflowr/notebooks) ## Curators [Marc Lelarge](https://www.di.ens.fr/~lelarge/), [Andrei Bursuc](https://abursuc.github.io/) with [Jill-Jênn Vie](https://jill-jenn.net/)