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[ADD] day3 #25

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32 changes: 32 additions & 0 deletions AI/day03/README.md
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# ~ PoC AI Pool 2024 ~

- ## Day 2: Neural Networks from Scratch
- ### Module 1: Linear Regression
- **folder:** [1 - Convolutional Neural Network](1%20-%20Convolutional%20Neural%20Network)
- ### Module 2: Logistic Regression
- **folder:** [2 - My nn Torch](2%20-%20My%20nn%20Torch)
- ### Module 3: Deep Learning
- **folder:** [3 - VAE-GAN](3%20-%20VAE-GAN)

---

**Hooray : You've made it to AI !**
On today's menu, we'll enter the wonderful world of machine learning with two major algorithms : Linear and Logistic Regression, followed by the modern approach of Deep Learning using PyTorch !

> Here's a list of resources that we believe can be useful to follow along (and that we've ourselves used to learn these topics before being able to write the subjects):

## Module 1

- [CNN](https://towardsdatascience.com/convolutional-neural-networks-explained-9cc5188c4939)
- [Custom nn module](https://pytorch.org/tutorials/beginner/nn_tutorial.html)

## Module 2

- [nn.Linear](https://pytorch.org/docs/stable/generated/torch.nn.Linear.html)
- [nn.Conv2d](https://pytorch.org/docs/stable/generated/torch.nn.Conv2d.html)

## Module 3

- [VAE](https://towardsdatascience.com/understanding-variational-autoencoders-vaes-f70510919f73)
- [GAN](https://towardsdatascience.com/gan-by-example-using-keras-on-tensorflow-backend-1a6d515a60d0)
- [VAE-GAN](https://wandb.ai/shambhavicodes/vae-gan/reports/An-Introduction-to-VAE-GANs--VmlldzoxMTcxMjM5)
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