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MITDeepLearning/introtodeeplearning ★ 8760 4564 DATA_RESEARCH

This repository contains educational labs for MIT's Introduction to Deep Learning course (6.S191). It consists of Jupyter notebooks covering deep learning fundamentals (Lab1: music generation with RNNs), computer vision (Lab2: MNIST classification and facial detection with VAEs), and LLM fine-tuning (Lab3: style adaptation using LoRA). The repository also includes extra labs for reinforcement learning and uncertainty quantification. While structured as educational material, the labs involve substantive data processing, model training, and evaluation pipelines. The mitdeeplearning package provides reusable utilities for training visualization and data handling. The code assumes execution in Google Colab with GPU access and relies on external APIs (Comet ML, OpenRouter) and datasets hosted on third-party services (Dropbox).

RATING: 6.5/10 REPRO: 5.0/10 MAINT: maintained DRIFT: medium
#education #deep-learning #jupyter-notebooks #llm-finetuning #computer-vision #reinforcement-learning #mit #neural-networks #tensorflow #tensorflow-tutorials #music-generation #deep-reinforcement-learning #deeplearning #pytorch #pytorch-tutorial
▸ 1 reusable components found
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