Personal Artificial Intelligence Resources List.
- Pre-Trained Models
- Deep Learning
- General Purpose Machine Learning
- Natural Language Processing
- Time Series Forecasting
- Statistical and Probabilistic Modelling
- Auto Machine Learning
- Feature Engineering
- Model Management
- Diagnostic, Inpection or Interpretation
- Data Visualization
- Misc
- Tutorials and Examples
- Lists
- audio-pretrained-model - A collection of Audio and Speech pre-trained models.
- awesome-deeplearning - Pre-trained models from the awesome-deeplearning repository.
- coreml-models - Largest list of models for Core ML (for iOS 11+).
- cv-pretrained-model - A collection of computer vision pre-trained models.
- efficientnet-pytorch - A PyTorch implementation of EfficientNet and EfficientNetV2.
- huggingface - Browse the model hub to discover, experiment and contribute to new state of the art models.
- layout-parser - A unified toolkit for Deep Learning Based Document Image Analysis.
- mmf - A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)
- modelzoo - Models and code that perform audio processing, speech synthesis, and other audio related tasks.
- nlp-pretrained-model - A collection of Natural language processing pre-trained models.
- nlp-recipes - Natural Language Processing Best Practices & Examples.
- openvino - Pre-trained Deep Learning models and demos (high quality and extremely fast).
- PaddlePaddle - Awesome pre-trained models toolkit based on PaddlePaddle.
- pyannote-audio - Neural building blocks for speaker and speech detection.
- pytorch-image-models - PyTorch image models, scripts, pretrained weights
- stylegan - A collection of pre-trained StyleGAN models to download.
- tfhub - Search and discover hundreds of trained, ready-to-deploy machine learning models.
- amazon-dsstne - Deep Scalable Sparse Tensor Network Engine.
- caffe - A fast open framework for deep learning.
- chainer - A flexible framework of neural networks for deep learning.
- cntk - An open source deep-learning toolkit.
- deepdetect - It makes state of the art machine learning easy to work with and integrate into existing applications.
- deeplearning4j - Open-source, distributed, scientific computing for the JVM.
- fastai - The fast.ai deep learning library, lessons, and tutorials.
- gym - A toolkit for developing and comparing reinforcement learning algorithms.
- keras - Deep Learning for humans.
- mxnet - A flexible and efficient library for deep learning.
- neon - Intel® Nervana™ reference deep learning framework.
- neupy - NeuPy is a Python library for Artificial Neural Networks and Deep Learning.
- neural-enhance - Super Resolution for images using deep learning.
- Paddle - PArallel Distributed Deep LEarning.
- singa - Distributed deep learning system.
- sonnet - TensorFlow-based neural network library.
- swflow - Simplified interface for TensorFlow for Deep Learning.
- tensorflow - Computation using data flow graphs for scalable - machine learning.
- tensorpack - A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility.
- tflearn - Deep learning library featuring a higher-level API for TensorFlow.
- aerosolve - A machine learning package built for humans.
- catboost - An open-source gradient boosting library with categorical features support.
- dmtk - Microsoft Distributed Machine Learning Toolkit.
- fastFM - fastFM: A Library for Factorization Machines.
- fklearn - Functional Machine Learning.
- h2o - Open Source Fast Scalable Machine Learning Platform For Smarter Applications.
- imbalanced-learn - A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning.
- JSAT - Java Statistical Analysis Tool, a Java library for Machine Learning.
- libffm - A Library for Field-aware Factorization Machines.
- libfm - Library for factorization machines.
- LightGBM - A fast, distributed, high performance gradient boosting framework based on decision tree algorithms.
- madlib - It is an open-source library for scalable in-database analytics.
- metric-learn - Metric learning algorithms in Python.
- mlens - ML-Ensemble – high performance ensemble learning.
- mllib - MLlib is Apache Spark's scalable machine learning library.
- moa - It is an open source framework for Big Data stream mining.
- orange3 - Interactive data analysis.
- pycobra - Python library implementing ensemble methods and visualisation tools including Voronoi tesselations.
- pyod - A Python Toolbox for Scalable Outlier Detection (Anomaly Detection).
- rep - Machine Learning toolbox for Humans.
- scikit-learn - Machine learning in Python.
- shogun - Unified and efficient Machine Learning since 1999.
- weka - It is a collection of machine learning algorithms for data mining tasks.
- xgboost - Scalable, Portable and Distributed Gradient Boosting Library.
- allennlp - An open-source NLP research library, built on PyTorch.
- anago - A Python library for sequence labeling implemented in Keras.
- dimsum16 - Detecting Minimal Semantic Units and their Meanings - (DiMSUM).
- finetune - Scikit-learn style model finetuning for NLP.
- flashtext - Extract Keywords from sentence or Replace keywords in sentences.
- fuzzywuzzy - Fuzzy String Matching in Python.
- gensim - Topic Modelling for Humans.
- gluon - A toolkit that enables easy text preprocessing to help you speed up your NLP research.
- Kashgari - NLP Transfer learning framework for text-labeling and text-classification.
- magnitude - A fast, efficient universal vector embedding utility package.
- mallet - It is a Java-based package for machine learning applications to text.
- nltk - Natural Language Toolkit.
- rasa - Open source machine learning framework to automate text- and voice-based conversations.
- senpy - A sentiment and emotion analysis server in Python.
- snips-nlu - Snips Python library to extract meaning from text.
- textacy - A Python library for performing a variety of NLP tasks.
- textgenrnn - Easily train your own text-generating neural network on any text dataset.
- word2vec - Python interface to Google word2vec.
- pmdarima - Time series analysis for Python.
- prophet - A procedure for forecasting time series data based on an additive model.
- pyflux - Open source time series library for Python.
- scikit-hts - Hierarchical time series forecasting for humans.
- statsmodels.tsa - Time Series analysis from statsmodels package.
- tsfresh - Automatic extraction of relevant features from time series.
- BayesianOptimization - A Python implementation of global optimization with gaussian processes.
- dowhy - A Python library for causal inference that supports explicit modeling and testing of causal assumptions.
- edward - A probabilistic programming language in TensorFlow.
- hmmlearn - Hidden Markov Models in Python, with scikit-learn like API.
- lifelines - Survival analysis in Python.
- mord - Ordinal regression algorithms.
- pomegranate - Fast, flexible and easy to use probabilistic modelling in Python.
- pyglmnet - Python implementation of elastic-net regularized generalized linear models.
- pymc3 - Probabilistic Programming in Python.
- python-mle - A Python package for performing Maximum Likelihood Estimates.
- RoBo - A Robust Bayesian Optimization framework.
- statsmodels - Statistical modeling and econometrics in Python.
- tea-lang - DSL for experimental design and statistical analysis.
- adanet - AdaNet is a lightweight TensorFlow-based framework for AutoML.
- AlphaPy - Automated Machine Learning AutoML for Python.
- auto-sklearn - Automated Machine Learning with scikit-learn.
- auto_ml - Automated machine learning for analytics & production.
- autokeras - Accessible AutoML for deep learning.
- automl-gs - AutoML tool that offers a zero code/model definition interface to getting an optimized model.
- diaml - Semi-automated machine learning pipelines.
- ludwig - Ludwig is a toolbox that allows to train deep learning models without coding.
- MLBox - It is a powerful Automated Machine Learning python library.
- onepanel-automl - Onepanel AutoML.
- optuna - A hyperparameter optimization framework.
- pycaret - An open-source, low-code machine learning library in Python.
- SMAC3 - Sequential Model-based Algorithm Configuration.
- TPOT - Tree-Based Pipeline Optimization Tool.
- TransmogrifAI - Automated machine learning for structured data.
- xcessiv - A web-based application for automated hyperparameter tuning and stacked ensembling in Python.
- categorical-encoding - A library of sklearn compatible categorical variable encoders.
- datacleaner - A Python tool that automatically cleans data sets and readies them for analysis.
- feature-selector - Feature selector is a tool for dimensionality reduction of machine learning datasets.
- featuretools - Automated feature engineering.
- hypertools - A Python toolbox for gaining geometric insights into high-dimensional data.
- umap - A dimension reduction technique that can be used for visualisation.
- cookiecutter-ds - Logical and flexible project structure for doing and sharing data science work.
- ds-process-management - Resources for Data Science Process management.
- dvc - Data & models versioning for ML projects, make them shareable and reproducible.
- firefly - Function as a service.
- hopsworks - Full-stack platform for scale-out data science.
- kedro - A Python library for building robust production-ready data and analytics pipelines.
- lore - A python framework to make machine learning approachable.
- marvin - The toolbox helps data scientists to develop, test, and run marvin engines.
- metaflow - Build and manage real-life data science projects with ease.
- mlflow - Open source platform for the machine learning lifecycle.
- anchor - High-Precision Model-Agnostic Explanations.
- ann-visualizer - A python library for visualizing Artificial Neural Networks with Keras.
- awesome-interpretable-machine-learning - Opinionated list of resources facilitating model interpretability.
- eli5 - A library for debugging/inspecting machine learning classifiers and explaining their predictions.
- explainerdashboard - Quickly build Explainable AI dashboards.
- interpret - Fit interpretable models. Explain blackbox machine learning.
- lime - Explaining the predictions of any machine learning classifier.
- lucid - A collection of infrastructure and tools for research in neural network interpretability.
- PDPbox - Python partial dependence plot toolbox.
- SHAP - A unified approach to explain the output of any machine learning model.
- what-if-tool - Easy-to-use interface for expanding understanding of a black-box classification/regression model.
- yellowbrick - Visual analysis and diagnostic tools to facilitate machine learning model selection.
- altair - Declarative statistical visualization library for Python.
- animatplot - A python package for animating plots build on matplotlib.
- bokeh - Interactive Web Plotting for Python.
- chartify - Python library that makes it easy for data scientists to create charts.
- dash - Interactive, Reactive Web Apps for Python.
- folium - Python Data to Leaflet.js Maps.
- holoviews - Stop plotting your data - annotate your data and let it visualize itself.
- ipyvolume - 3d plotting for Python in the Jupyter notebook based on IPython widgets using WebGL.
- matplotlib - Plotting with Python.
- plotnine - A grammar of graphics for Python.
- scattertext - Beautiful visualizations of how language differs among document types.
- scikit-plot - An intuitive library to add plotting functionality to scikit-learn objects.
- seaborn - Statistical data visualization.
- speedml - Speedml is a Python package to speed start machine learning projects.
- streamlit - The fastest way to build custom ML tools.
- vega - A visualization grammar.
- veles - Binary data analysis and visualization tool.
- vispy - Interactive scientific visualization that is designed to be fast, scalable, and easy to use.
- wordcloud - A little word cloud generator in Python.
- deap - Distributed Evolutionary Algorithms in Python
- feather - Fast, interoperable binary data frame storage for Python and R.
- gplearn - Genetic Programming in Python.
- gtdata - Download and play with key datasets from Google Trend.
- librosa - Python library for audio and music analysis.
- m2cgen - Transform ML models into a native code with zero dependencies
- mahout - It is a distributed linear algebra framework and mathematically expressive Scala DSL.
- mlxtend - A library of extension and helper modules for Python's data analysis and machine learning libraries.
- pandas-profiling - Create HTML profiling reports from pandas DataFrame objects.
- pandas_flavor - The easy way to write your own flavor of Pandas.
- pythia - A modular framework for Visual Question Answering research from Facebook AI Research (FAIR).
- sklearn-pandas - Pandas integration with sklearn.
- snorkel - A system for quickly generating training data with weak supervision.
- traces - A Python library for unevenly-spaced time series analysis.
- 100 Days of ML Code - 100 Days of ML Coding.
- BayesianModelling - A python tutorial on bayesian modeling techniques.
- ds-ipython-notebooks - Data science Python notebooks.
- EffectiveTensorflow - TensorFlow tutorials and best practices.
- kaggle-past-solutions - A searchable compilation of Kaggle past solutions.
- MLAlgorithms - Minimal and clean examples of machine learning algorithms implementations.
- MLFromScratch - Machine Learning From Scratch.
- MLPB - Machine Learning Problem Bible.
- tf-models - Models and examples built with TensorFlow.
- Virgilio - Your new Mentor for Data Science E-Learning.
- awesome-datascience - An awesome Data Science repository to learn and apply for real world problems.
- awesome-deep-learning-papers - The most cited deep learning papers.
- awesome-machine-learning - A curated list of awesome Machine Learning frameworks, libraries and software.
- Deep Learning Drizzle - Learn Deep Lerning from exciting lectures.
- Deep-Learning-Papers-Reading-Roadmap - Deep Learning papers reading roadmap.
- Deep-Learning-World - Organized Resources for Deep Learning Researchers and Developers.
- ml4se - A complete daily plan for studying to become a machine learning engineer.
- ossu-data-science - Path to a free self-taught education in Data Science!
- python-machine-learning-book - The "Python Machine Learning (1st edition)" book code repository and info resource.