machinelearning

Machine Learning and Deep Learning

Python:

Survey ritchieng/the-incredible-pytorch at pythonrepo.com

3.5.1. Machine Learning

Julia: MLJ is enough

alan-turing-institute/MLJ.jl: A Julia machine learning framework

JuliaML

JuliaAI

Evovest/EvoTrees.jl: Boosted trees in Julia

Dimention Reduction:madeleineudell/LowRankModels.jl: LowRankModels.jl is a julia package for modeling and fitting generalized low rank models.

JuliaStats/MultivariateStats.jl: A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)

Linear RegressionJuliaAI/MLJLinearModels.jl: Generalized Linear Regressions Models (penalized regressions, robust regressions, ...)

gerdm/pknn.jl: Probabilistic k-nearest neighbours

IBM/AutoMLPipeline.jl: A package that makes it trivial to create and evaluate machine learning pipeline architectures.

Python:

scikit-learn: machine learning in Python — scikit-learn 1.0.1 documentation

DistrictDataLabs/yellowbrick: Visual analysis and diagnostic tools to facilitate machine learning model selection.

automl/auto-sklearn: Automated Machine Learning with scikit-learn

h2oai/h2o-3: H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

pycaret/pycaret: An open-source, low-code machine learning library in Python

nubank/fklearn: fklearn: Functional Machine Learning

wecarsoniv/augmented-pca: Repository for the AugmentedPCA Python package.

Data Generation

snorkel-team/snorkel: A system for quickly generating training data with weak supervision

lk-geimfari/mimesis: Mimesis is a high-performance fake data generator for Python, which provides data for a variety of purposes in a variety of languages.

Deep Learning

Julia: Flux and Knet

FluxML/Flux.jl: Relax! Flux is the ML library that doesn't make you tensor

sdobber/FluxArchitectures.jl: Complex neural network examples for Flux.jl

denizyuret/Knet.jl: Koç University deep learning framework.

Python: Jax, Pytorch, Tensorflow

Reviewn2cholas/awesome-jax: JAX - A curated list of resources https://github.com/google/jax

google/jax: Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

pytorch/pytorch: Tensors and Dynamic neural networks in Python with strong GPU acceleration

tensorflow/tensorflow: An Open Source Machine Learning Framework for Everyone

catalyst-team/catalyst: Accelerated deep learning R&D

murufeng/awesome_lightweight_networks: MobileNetV1-V2，MobileNeXt，GhostNet，AdderNet，ShuffleNetV1-V2，Mobile+ViT etc. ⭐⭐⭐⭐⭐

Review: Chen-Cai-OSU/awesome-equivariant-network: Paper list for equivariant neural network

3.5.3. Reinforce Learning

Julia:

JuliaPOMDP

JuliaReinforcementLearning

Python:

ray-project/ray: An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

tensorlayer/tensorlayer: Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥

pfnet/pfrl: PFRL: a PyTorch-based deep reinforcement learning library

thu-ml/tianshou: An elegant PyTorch deep reinforcement learning library.

3.5.4. GNN

Julia:

CarloLucibello/GraphNeuralNetworks.jl: Graph Neural Networks in Julia

FluxML/GeometricFlux.jl: Geometric Deep Learning for Flux

Python:

pyg-team/pytorch_geometric: Graph Neural Network Library for PyTorch

benedekrozemberczki/pytorch_geometric_temporal: PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

dmlc/dgl: Python package built to ease deep learning on graph, on top of existing DL frameworks.

THUDM/cogdl: CogDL: An Extensive Toolkit for Deep Learning on Graphs

3.5.5. Transformer

Julia:

chengchingwen/Transformers.jl: Julia Implementation of Transformer models

Python:

huggingface/transformers: 🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.

3.5.6. Transfer Learning

Surveyjindongwang/transferlearning: Transfer learning / domain adaptation / domain generalization / multi-task learning etc. papers, codes. datasets, applications, tutorials.-迁移学习

3.5.7. Neural Tangent

Python:

google/neural-tangents: Fast and Easy Infinite Neural Networks in Python

3.5.8. Visulization

Python:

ashishpatel26/Tools-to-Design-or-Visualize-Architecture-of-Neural-Network: Tools to Design or Visualize Architecture of Neural Network

julrog/nn_vis: A project for processing neural networks and rendering to gain insights on the architecture and parameters of a model through a decluttered representation.

PowerPointsdair-ai/ml-visuals: 🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.

Semi-supervised Learning

Python:

TorchSSL/TorchSSL: A PyTorch-based library for semi-supervised learning (NeurIPS'21)