Repository for the Deep Learning and Generative AI laboratory, "Alexandru Ioan Cuza" University, Faculty of Computer Science, Master degree.
Companion repository: AI-Learning-Hub
Start with the 2026 local setup and run the included offline CPU smoke check.
- AI-Learning-Hub/how_to/install_pytorch
- AI-Learning-Hub/how_to/use_google_colab
- AI-Learning-Hub/how_to/use_kaggle
- Lab01: Intro, Advanced Tensor Operations, PyTorch Recap (Homework 1: Multi Layer Perceptron + Backpropagation)
- Lab02: Efficient Training and Inference, Test Time Augmentation
- Lab03: Cpp Modules, Distributed Data Parallel, SAM Optimizer, Muon Optimizer, Tensorboard, Weights and biases, AlexNet, ResNet, Batch Normalization (Homework 2: Training VGG-13)
- Lab04: Advanced CV Architectures: AlexNet, VGG, Inception, ResNet, MobileNet, Squeeze-and-Excitation, EfficientNetV2 and RegNet.
- Lab05: Object Detection: slides/papers and a 2-hour Fast R-CNN practical notebook (Colab) (Homework 3: Complex experiments on Noisy CIFAR-100).