DAY 20 – Introduction to Variational Autoencoders (VAE)
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21 Days Agenda for Generative AI
Day 1: Introduction to Generative AI, Deep learning, Pytorch installation
Day 2: Pytorch basics – Tensor creation, reshaping, device handling
Day 3: Deep learning concepts – Neural networks, Activation functions, optimizers, loss functions
Day 4: Creating a basic neural network with Pytorch
Day 5: Breast Cancer prediction on using ANN with PyTorch
Day 6: Flight Fare Prediction using ANN Wisconsin dataset with PyTorch
Day 7: Introduction to computer vision
Day 8: Computer vision tools in PyTorch and opencv
Day 9: Introduction to CNN in Pytorch
Day 10: Plant Disease detection using CNN with Pytorch
Day 11: Introduction to GANs, types of GANs, Applications
Day 12: GAN – Handwritten Digits Generation using PyTorch GAN
Day 13: DCGAN – Realistic Face Generation with DCGAN on Celebi
Day 14: WGAN – High-Quality Artwork Generation with Wasserstein GAN on CIFAR-10
Day 15: CGAN – Conditional Image Generation with CGAN on FashionMNIST
Day 16: Pix2Pix GAN – Image-to-Image Translation on Cityscapes
Day 17: Style GAN – Generating Artistic Images with Style GAN
Day 18: SR-GAN – Image Resolution Enhancement with SR-GAN on DIV2K
Day 19: Pro-GAN – Progressive High-Quality Faces with Pro-GAN on CelebA-HQ
Day 20: Introduction to Variational Autoencoders (VAE)
Day 21: Image generation using VA
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