In 2024, LauzHack organized its first bootcamp on deep learning.

Syllabus, slides, and Jupyter notebooks can be found on GitHub: https://github.com/LauzHack/deep-learning-bootcamp/

Recording links:

Day1-Part1: Introduction to Python, Training, Optimizers, Learning Rate https://youtu.be/qtY6RTqKOsE
Day1-Part2: Improving Python and Git Workflow: https://youtu.be/okxaTuBdDuY
Day2-Part1: Fully-Connected and Convolutional Neural Networks, ResNet https://youtu.be/3EDUGwWxZFw
Day2-Part2: Recurrent Neural Networks, Normalization Techniques https://youtu.be/1X_hZjJ95kc
Day3-Part1: Transformer and Attention Mechanism https://youtu.be/SleVoySdPoA
Day3-Part2: Improved Logging with WandB, R&D Coding Techniques https://youtu.be/sEA-Js5ZHxU
Day4-Part1: Introduction to Deep Learning in Audio and Tasks Overview https://youtu.be/YuImUy6vPFs
Day4-Part2: Voice Deepfake Detection and Graph Neural Networks https://youtu.be/oim5h1_4T5I
Day5-Part1: Classic CV methods, Image Recognition, and Object Detection https://youtu.be/bMZsx7wl9fM
Day5-Part2: Object Detection and Image Segmentation https://youtu.be/oR6yMQ-1r7A
Day6-Part1: Efficient Single-GPU Training and Distributed Deep Learning https://youtu.be/p234xhpmzqw
Day6-Part2: On-Device Learning, Domain Adaptation, and Continuous Learning https://youtu.be/vNTPCQnejHI
Day7-Part1: Introduction to NLP: Tokenization, Embeddings, CBOW, BERT https://youtu.be/C5Hac9nz5Hs
Day7-Part2: BERT, Knowledge Distillation, GPT and LLMs https://youtu.be/wCWxyrm0Mg8
Day8-Part2: Explainable AI (Intrinsic, In-Hoc, Post-Hoc Methods), Multi-Modal https://youtu.be/eVs008-lkLM
Day8-Part3: Multi-Modal Networks, Flamingo, CLIP, 3D CV https://youtu.be/E6NpC4WuGdA
Day9: Fine-Tuning, Transfer Learning, Hugging Face https://youtu.be/wfwzoFlAbuw

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