/Great-Deep-Learning-Tutorials

A Great Collection of Deep Learning Tutorials and Repositories

MIT LicenseMIT

Great-Deep-Learning-Tutorials

A Great Collection of Deep Learning Tutorials and Repositories

General Deep Learning Tutorials:

Deep Learning Useful Resources for Computer Vision:

Deep Learning Useful Resources for Natural Language Processing (NLP):

Deep Learning Useful Resources for Spoken Language Processing (Speech Processing):

Deep Learning & Machine Learning Useful Resources for General Data Science Tasks:

General Notes about Generative AI:

Quantization & Distillation of Deep Learning Models:

AutoML:

Diffusion Models:

Multimodal Deep Learning:

Deep Reasoning:

Deep Reinforcement Learning (Great Courses & Tutorials):

Graph Neural Networks:

Graph Neural Networks Frameworks:

Best Practices for Training Deep Models:

General Notes for Training Deep Models:

PyTorch Lightening Notes & Accumulate Gradients:

Loss Functions:

Imbalanced Dataset Handling:

Weight Initialization:

Batch Normalization:

Learning Rate Scheduling & Initialization:

Early Stopping:

Tuning Guide Recipes:

Training Optimizer:

PyTorch running & training on TPU (colab):

Evaluation Metrics:

Validating ML Models:

Optimizing models when run on GPU:

Conferences News:

Deep Learning Frameworks and Infrustructures:

Great Libraries:

Great Models:

Deep Model Conversion:

Great Deep Learning Repositories (for learning DL-based programming):

PyTorch High-Level Libraries:

Annotation Tools:

Other: