A Great Collection of Deep Learning Tutorials and Repositories
- Browse state-of-the-art Deep Learning based Papers with their associated codes [Extremely Fantastic]
- Deep-Learning-Roadmap
- DeepLizard [Good Tutorials for Deep Learning]
- Sebastian Ruder - Blog [Great NLP & Deep Learning Posts]
- Jeremy Jordan - Blog
- Excellent Blog
- Torchvision Release Notes [Important]
- The 6 most useful Machine Learning projects of the past year (2018)
- ResNet Review
- Receptive Field Estimation [Great]
- An overview of gradient descent optimization algorithms [Useful]
- How to decide on learning rate
- Overview of State-of-the-art Machine Learning Algorithms per Discipline per Task
- Awesome Machine Learning and AI Courses
- PyTorch Book
- Great Deep Learning Resources for NLP Tasks [Excellent]
- Quantization
- Neural Network Distiller
- Introduction to Quantization on PyTorch [Excellent]
- Dynamic Quantization in PyTorch
- Static Quantization in PyTorch
- Intel(R) Math Kernel Library - Intel MKL-DNN
- Intel MKL-Dnn
- ONNX Float32 to Float16
- Neural Network Quantization Introduction [Tutorial]
- Quantization in Deep Learning [Tutorial]
- Speeding up Deep Learning with Quantization [Tutorial]
- Knowledge Distillation in Deep Learning
- Model Distillation Techniques for Deep Learning
- MMRazor: model compression toolkit [Great]
- How to Prepare Categorical Data for Deep Learning in Python
- Handling Categorical Data in ML Models
- Encoding Categorical Data
- Lime: Explaining the predictions of any machine learning classifier
- Lime Tutorial: Building Trust in Machine Learning Models (using LIME in Python)
- Missing Values: End-to-End Introduction to Handling Missing Values
- Cracking the Data Science Interview
- Data Engineer Interview Questions Python
- Facebook Data Scientist Interview Questions
- Interview Guides: Facebook Data Scientist
- Meta (Facebook) Data Science Interview Questions and Solutions
- Deep Learning Recommendation Model for Personalization and Recommendation Systems - DLRM
- DLRM: An advanced, open source deep learning recommendation model
- LightFM
- Neural Recommendation Algorithms
- Build a Recommendation Engine With Collaborative Filtering [Great]
- NCF - Neural Collaborative Filtering
- Using Neural Networks for your Recommender System [Great]
- Neural Collaborative Filtering
- AWS Personalized Recommendation Model
- A Free course in Deep Reinforcement Learning from beginner to expert [Great]
- Deep Reinforcement Learning Algorithms with PyTorch
- Deep Reinforcement Learning - CS 285 Berkeley Course
- solutions to UC Berkeley CS 285
- Reinforcement Learning: An Introduction - main book in this field
- CS234: Reinforcement Learning Course
- Introduction to Reinforcement Learning Course - by DeepMind
- An Introduction to Graph Neural Networks
- How to Train Graph Convolutional Network Models in a Graph Database
- A comprehensive survey on graph neural networks
- Graph Neural Networks: A Review of Methods and Applications
- Spektral
- Deep Graph Library - DGL
- PyTorch Geometric - PyG
- ptgnn: A PyTorch GNN Library
- Graph Data Augmentation Papers
- Batch Normalization in Neural Networks
- Batch Normalization and Dropout in Neural Networks
- Difference between Local Response Normalization and Batch Normalization
- Automated Learning Rate Suggester
- Learning Rate Finder - fastai
- Cyclical Learning Rates for Training Neural Networks
- ignite - Example of FastaiLRFinder
- Find Learning Rate - a gist code
- Learning rate finder - PyTorch Lightning
- RAdam - On the Variance of the Adaptive Learning Rate and Beyond
- Early Stopping in PyTorch - Bjarten
- Catalyst - Early Stopping
- ignite - Early Stopping
- PyTorch High-Level Training Sample
- PyTorch Discussion about Early Stopping
- PyTorch Tuning Guide Tutorial
- PyTorch memory leak with dynamic size tensor input
- Karpathy: A Recipe for Training Neural Networks
- Latest Computer Vision Trends from CVPR 2019
- Interesting 2019 CVPR papers
- Summaries of CVPR papers on ShortScience.org
- Summaries of ICCV papers on ShortScience.org
- Summaries of ECCV papers on ShortScience.org
- set-up a Paperspace GPU Server
- Distributed ML with OpenMPI
- Tensorflow 2.0 vs Mxnet
- TensorFlow is dead, long live TensorFlow!
- Skorch - A scikit-learn compatible neural network library that wraps PyTorch
- Hummingbird - traditional ML models into tensor computations via PyTorch
- BoTorch - Bayesian Optimization in PyTorch
- torchvision 0.3: segmentation, detection models, new datasets and more
- TorchAudio: an audio library for PyTorch
- AudTorch
- TorchAudio-Contrib
- fastText - Facebook AI Research (FAIR)
- Fairseq - Facebook AI Research (FAIR)
- ParlAI - dialogue models - Facebook AI Research (FAIR)
- DALI - highly optimized engine for data pre-processing
- Netron - GitHub [Visualizer for deep learning Models (Excellent)]
- Netron - Web Site
- JupyterLab GPU Dashboards [Good]
- PyTorch Hub
- Neural Structured Learning (NSL) in TensorFlow
- Pywick - High-Level Training framework for Pytorch
- torchbearer: A model fitting library for PyTorch
- torchlayers - Shape inference for PyTorch (like in Keras)
- torchtext - GitHub
- torchtext - Doc
- Optuna - hyperparameter optimization framework
- PyTorchLightning
- Nvidia - runx - An experiment management tool
- MLogger: a Machine Learning logger
- ClearML - ML/DL development and production suite
- Lime: Explaining the predictions of any ML classifier
- Microsoft UniLM AI [Great]
- NVIDIA NeMo - toolkit for creating Conversational AI (ASR, TTS, and NLP)
- ResNext WSL [Great Pretrained Model]
- Semi-Weakly Supervised (SWSL) ImageNet Models [Great Pretrained Model]
- Deep High-Resolution Representation Learning (HRNet)
- deeplearning-models - PyTorch & TensorFlow Learning [Very Excellent Repository]
- PyTorch Image Models [Great]
- 5 Advanced PyTorch Tools to Level up Your Workflow [Interesting]