Awesome Open Source
Awesome Open Source

Awesome Data Science with Python

A curated list of awesome resources for practicing data science using Python, including not only libraries, but also links to tutorials, code snippets, blog posts and talks.


pandas - Data structures built on top of numpy.
scikit-learn - Core ML library.
matplotlib - Plotting library.
seaborn - Data visualization library based on matplotlib.
datatile - Basic statistics using DataFrameSummary(df).summary().
pandas_profiling - Descriptive statistics using ProfileReport.
sklearn_pandas - Helpful DataFrameMapper class.
missingno - Missing data visualization.
rainbow-csv - Plugin to display .csv files with nice colors.

Environment and Jupyter

General Jupyter Tricks
Fixing environment: link
Python debugger (pdb) - blog post, video, cheatsheet
cookiecutter-data-science - Project template for data science projects.
nteract - Open Jupyter Notebooks with doubleclick.
papermill - Parameterize and execute Jupyter notebooks, tutorial.
nbdime - Diff two notebook files, Alternative GitHub App: ReviewNB.
RISE - Turn Jupyter notebooks into presentations.
qgrid - Pandas DataFrame sorting.
pivottablejs - Drag n drop Pivot Tables and Charts for jupyter notebooks.
itables - Interactive tables in Jupyter.
jupyter-datatables - Interactive tables in Jupyter.
debugger - Visual debugger for Jupyter.
nbcommands - View and search notebooks from terminal.
handcalcs - More convenient way of writing mathematical equations in Jupyter.
notebooker - Productionize and schedule Jupyter Notebooks.
bamboolib - Intuitive GUI for tables.
voila - Turn Jupyter notebooks into standalone web applications.
voila-gridstack - Voila grid layout.

Pandas Tricks, Alternatives and Additions

Pandas Tricks
Using df.pipe() (video)
pandasvault - Large collection of pandas tricks.
modin - Parallelization library for faster pandas DataFrame.
vaex - Out-of-Core DataFrames.
pandarallel - Parallelize pandas operations.
xarray - Extends pandas to n-dimensional arrays.
swifter - Apply any function to a pandas dataframe faster.
pandas_flavor - Write custom accessors like .str and .dt.
pandas-log - Find business logic issues and performance issues in pandas.
pandapy - Additional features for pandas.
lux - Dataframe visualization within Jupyter.
dtale - View and analyze Pandas data structures, integrating with Jupyter.
polars - Multi-threaded alternative to pandas.
duckdb - Efficiently run SQL queries on pandas DataFrame.

Scikit-Learn Alternatives

scikit-learn-intelex - Intel extension for scikit-learn for speed.


drawdata - Quickly draw some points and export them as csv, website.
tqdm - Progress bars for for-loops. Also supports pandas apply().
icecream - Simple debugging output.
loguru - Python logging.
pyprojroot - Helpful here() command from R.
intake - Loading datasets made easier, talk.


textract - Extract text from any document.
camelot - Extract text from PDF.

Big Data

spark - DataFrame for big data, cheatsheet, tutorial.
sparkit-learn, spark-deep-learning - ML frameworks for spark.
koalas - Pandas API on Apache Spark.
dask, dask-ml - Pandas DataFrame for big data and machine learning library, resources, talk1, talk2, notebooks, videos.
dask-gateway - Managing dask clusters.
turicreate - Helpful SFrame class for out-of-memory dataframes.
h2o - Helpful H2OFrame class for out-of-memory dataframes.
datatable - Data Table for big data support.
cuDF - GPU DataFrame Library, Intro.
ray - Flexible, high-performance distributed execution framework.
mars - Tensor-based unified framework for large-scale data computation.
bottleneck - Fast NumPy array functions written in C.
bolz - A columnar data container that can be compressed.
cupy - NumPy-like API accelerated with CUDA.
petastorm - Data access library for parquet files by Uber.
zarr - Distributed numpy arrays.
NVTabular - Feature engineering and preprocessing library for tabular data by nvidia.
tensorstore - Reading and writing large multi-dimensional arrays (Google).

Distributed Systems

nextflow - Run scripts and workflow graphs in Docker image using Google Life Sciences, AWS Batch, Website.
dsub - Run batch computing tasks in Docker image in the Google Cloud.

Command line tools, CSV

ni - Command line tool for big data.
xsv - Command line tool for indexing, slicing, analyzing, splitting and joining CSV files.
csvkit - Another command line tool for CSV files.
csvsort - Sort large csv files.
tsv-utils - Tools for working with CSV files by ebay.
cheat - Make cheatsheets for command line commands.

Classical Statistics


phik - Correlation between categorical, ordinal and interval variables.


statsmodels - Statistical tests.
linearmodels - Instrumental variable and panel data models.
pingouin - Statistical tests. Pairwise correlation between columns of pandas DataFrame
scipy.stats - Statistical tests.
scikit-posthocs - Statistical post-hoc tests for pairwise multiple comparisons.
Bland-Altman Plot 1, 2 - Plot for agreement between two methods of measurement.
ANOVA, Tutorials: One-way, Two-way, Type 1,2,3 explained.

Statistical Tests

test_proportions_2indep - Proportion test.
G-Test - Alternative to chi-square test, power_divergence.

Comparing Two Populations

torch-two-sample - Friedman-Rafsky Test: Compare two population based on a multivariate generalization of the Runstest. Explanation, Application

Interim Analyses / Sequential Analysis / Stopping

Squential Analysis - Wikipedia.
Treatment Effects Monitoring - Design and Analysis of Clinical Trials PennState.
sequential - Exact Sequential Analysis for Poisson and Binomial Data (R package).
confseq - Uniform boundaries, confidence sequences, and always-valid p-values.


Great Overview over Visualizations
Dependent Propabilities
Null Hypothesis Significance Testing (NHST) and Sample Size Calculation
Cohen's d
Confidence Interval
Equivalence, non-inferiority and superiority testing
Bayesian two-sample t test
Distribution of p-values when comparing two groups
Understanding the t-distribution and its normal approximation


Inverse Propensity Weighting
Dealing with Selection Bias By Propensity Based Feature Selection


Modes, Medians and Means: A Unifying Perspective
Using Norms to Understand Linear Regression
Verifying the Assumptions of Linear Models
Mediation and Moderation Intro
Montgomery et al. - How conditioning on post-treatment variables can ruin your experiment and what to do about it
Greenland - Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations
Blume - Second-generation p-values: Improved rigor, reproducibility, & transparency in statistical analyses
Lindeløv - Common statistical tests are linear models
Chatruc - The Central Limit Theorem and its misuse
Al-Saleh - Properties of the Standard Deviation that are Rarely Mentioned in Classrooms
Wainer - The Most Dangerous Equation
Gigerenzer - The Bias Bias in Behavioral Economics
Cook - Estimating the chances of something that hasn’t happened yet


R Epidemics Consortium - Large tool suite for working with epidemiological data (R packages). Github
incidence2 - Computation, handling, visualisation and simple modelling of incidence (R package).
EpiEstim - Estimate time varying instantaneous reproduction number R during epidemics (R package) paper.
researchpy - Helpful summary_cont() function for summary statistics (Table 1).
zEpid - Epidemiology analysis package, Tutorial.
tipr - Sensitivity analyses for unmeasured confounders (R package).

Exploration and Cleaning

pandasgui - GUI for viewing, plotting and analyzing Pandas DataFrames.
janitor - Clean messy column names.
pandera - Data / Schema validation.
impyute - Imputations.
fancyimpute - Matrix completion and imputation algorithms.
imbalanced-learn - Resampling for imbalanced datasets.
tspreprocess - Time series preprocessing: Denoising, Compression, Resampling.
Kaggler - Utility functions (OneHotEncoder(min_obs=100))
pyupset - Visualizing intersecting sets.
pyemd - Earth Mover's Distance / Wasserstein distance, similarity between histograms. OpenCV implementation, POT implementation
littleballoffur - Sampling from graphs.

Noisy Labels

cleanlab - Machine learning with noisy labels, finding mislabeled data, and uncertainty quantification. Also see awesome list below.
doubtlab - Find bad or noisy labels.

Train / Test Split

iterative-stratification - Stratification of multilabel data.

Feature Engineering

sklearn - Pipeline, examples.
pdpipe - Pipelines for DataFrames.
scikit-lego - Custom transformers for pipelines.
skoot - Pipeline helper functions.
categorical-encoding - Categorical encoding of variables, vtreat (R package).
dirty_cat - Encoding dirty categorical variables.
patsy - R-like syntax for statistical models.
mlxtend - LDA.
featuretools - Automated feature engineering, example.
tsfresh - Time series feature engineering.
pypeln - Concurrent data pipelines.
feature_engine - Encoders, transformers, etc.
NVTabular - Feature engineering and preprocessing library for tabular data by nvidia.

Computer Vision

Intro to Computer Vision

Image Cleanup

Fiji - General purpose tool. Image viewer and image processing package.
napari - Multi-dimensional image viewer.
fiftyone - Viewer and tool for building high-quality datasets and computer vision models.
DivNoising - Unsupervised denoising method.
aydin - Image denoising.
unprocessing - Image denoising by reverting the image processing pipeline.

Microscopy / Segmentation


jump-cellpainting - Cellpainting dataset.
MedMNIST - Datasets for 2D and 3D Biomedical Image Classification.
CytoImageNet - Huge diverse dataset like ImageNet but for cell images.
cellpose dataset - Cell images.
Haghighi - Gene Expression and Morphology Profiles.
broadinstitute/lincs-profiling-complementarity - Cellpainting vs. L1000 assay.


Awesome Cytodata
BD Spectrum Viewer - Calculate spectral overlap, bleed through for fluorescence microscopy dyes.
Tree of Microscopy - Review of cell segmentation algorithms, Paper.
cellpose - Cell segmentation. Paper, Dataset.
skimage - Illumination correction (CLAHE).
cidre - Illumination correction method for optical microscopy.
BaSiCPy - Background and Shading Correction of Optical Microscopy Images, BaSiC.
ashlar - Whole-slide microscopy image stitching and registration.
CSBDeep - Image denoising, restoration and object detection, Project page.
mcmicro - Multiple-choice microscopy pipeline, Paper.
UnMicst - Identifying Cells and Segmenting Tissue.
stardist - Object Detection with Star-convex Shapes.
nnUnet - 3D biomedical image segmentation.
atomai - Deep and Machine Learning for Microscopy.
allencell - Tools for the 3D segmentation of intracellular structures.

Domain Adaptation / Batch-Effect Correction

Tran - A benchmark of batch-effect correction methods for single-cell RNA sequencing data, Code.
R Tutorial on correcting batch effects.
harmonypy - Fuzzy k-means and locally linear adjustments.
pyliger - Batch-effect correction, Example, R package.
nimfa - Nonnegative matrix factorization.
scgen - Batch removal. Doc.
CORAL - Correcting for Batch Effects Using Wasserstein Distance, Code, Paper.
adapt - Aweseome Domain Adaptation Python Toolbox.
pytorch-adapt - Various neural network models for domain adaptation.

Feature Engineering Images

skimage - Regionprops: area, eccentricity, extent.
mahotas - Zernike, Haralick, LBP, and TAS features.
pyradiomics - Radiomics features from medical imaging.
pyefd - Elliptical feature descriptor, approximating a contour with a Fourier series.

Feature Selection

Overview Paper, Talk, Repo
Blog post series - 1, 2, 3, 4
Tutorials - 1, 2
sklearn - Feature selection.
eli5 - Feature selection using permutation importance.
scikit-feature - Feature selection algorithms.
stability-selection - Stability selection.
scikit-rebate - Relief-based feature selection algorithms.
scikit-genetic - Genetic feature selection.
boruta_py - Feature selection, explaination, example.
Boruta-Shap - Boruta feature selection algorithm + shapley values.
linselect - Feature selection package.
mlxtend - Exhaustive feature selection.
BoostARoota - Xgboost feature selection algorithm.
INVASE - Instance-wise Variable Selection using Neural Networks.
SubTab - Subsetting Features of Tabular Data for Self-Supervised Representation Learning, AstraZeneca.
mrmr - Maximum Relevance and Minimum Redundancy Feature Selection, Website.
arfs - All Relevant Feature Selection.
VSURF - Variable Selection Using Random Forests (R package) doc.
FeatureSelectionGA - Feature Selection using Genetic Algorithm.

Subset Selection

apricot - Selecting subsets of data sets to train machine learning models quickly.
ducks - Index data for fast lookup by any combination of fields.

Dimensionality Reduction / Representation Learning


Check also the Clustering section and self-supervised learning section for ideas!

PCA - link
Autoencoder - link
Isomaps - link
LLE - link
Force-directed graph drawing - link
MDS - link
Diffusion Maps - link
t-SNE - link
NeRV - link, paper
MDR - link
UMAP - link
Random Projection - link
Ivis - link
SimCLR - link

Neural-network based

esvit - Vision Transformers for Representation Learning (Microsoft).
MCML - Semi-supervised dimensionality reduction of Multi-Class, Multi-Label data (sequencing data) paper.


Dangers of PCA (paper).
Talk, tsne intro. sklearn.manifold and sklearn.decomposition - PCA, t-SNE, MDS, Isomaps and others.
Additional plots for PCA - Factor Loadings, Cumulative Variance Explained, Correlation Circle Plot, Tweet
sklearn.random_projection - Johnson-Lindenstrauss lemma, Gaussian random projection, Sparse random projection.
sklearn.cross_decomposition - Partial least squares, supervised estimators for dimensionality reduction and regression.
prince - Dimensionality reduction, factor analysis (PCA, MCA, CA, FAMD).
Faster t-SNE implementations: lvdmaaten, MulticoreTSNE, FIt-SNE umap - Uniform Manifold Approximation and Projection, talk, explorer, explanation, parallel version.
humap - Hierarchical UMAP.
sleepwalk - Explore embeddings, interactive visualization (R package).
somoclu - Self-organizing map.
scikit-tda - Topological Data Analysis, paper, talk, talk, paper.
giotto-tda - Topological Data Analysis.
ivis - Dimensionality reduction using Siamese Networks.
trimap - Dimensionality reduction using triplets.
scanpy - Force-directed graph drawing, Diffusion Maps.
direpack - Projection pursuit, Sufficient dimension reduction, Robust M-estimators.
DBS - DatabionicSwarm (R package).
contrastive - Contrastive PCA.
scPCA - Sparse contrastive PCA (R package).
tmap - Visualization library for large, high-dimensional data sets.
lollipop - Linear Optimal Low Rank Projection.
linearsdr - Linear Sufficient Dimension Reduction (R package).
PHATE - Tool for visualizing high dimensional data.


iterative-stratification - Cross validators with stratification for multilabel data.
livelossplot - Live training loss plot in Jupyter Notebook.


All charts, Austrian monuments.
Better heatmaps and correlation plots.
Example notebooks for interactive visualizations(Plotly,Seaborn, Holoviz, Altair)
cufflinks - Dynamic visualization library, wrapper for plotly, medium, example.
physt - Better histograms, talk, notebook.
fast-histogram - Fast histograms.
matplotlib_venn - Venn diagrams, alternative.
joypy - Draw stacked density plots (=ridge plots), Ridge plots in seaborn.
mosaic plots - Categorical variable visualization, example.
scikit-plot - ROC curves and other visualizations for ML models.
yellowbrick - Visualizations for ML models (similar to scikit-plot).
bokeh - Interactive visualization library, Examples, Examples.
lets-plot - Plotting library.
animatplot - Animate plots build on matplotlib.
plotnine - ggplot for Python.
altair - Declarative statistical visualization library.
bqplot - Plotting library for IPython/Jupyter Notebooks.
hvplot - High-level plotting library built on top of holoviews.
dtreeviz - Decision tree visualization and model interpretation.
chartify - Generate charts.
VivaGraphJS - Graph visualization (JS package).
pm - Navigatable 3D graph visualization (JS package), example.
python-ternary - Triangle plots.
falcon - Interactive visualizations for big data.
hiplot - High dimensional Interactive Plotting.
visdom - Live Visualizations.
mpl-scatter-density - Scatter density plots. Alternative to 2d-histograms.
ComplexHeatmap - Complex heatmaps for multidimensional genomic data (R package).
largeVis - Visualize embeddings (t-SNE etc.) (R package).
proplot - Matplotlib wrapper.
morpheus - Broad Institute tool matrix visualization and analysis software. Source, Tutorial: 1, 2, Code.


palettable - Color palettes from colorbrewer2.
colorcet - Collection of perceptually uniform colormaps.
Named Colors Wheel - Color wheel for all named HTML colors.


superset - Dashboarding solution by Apache.
streamlit - Dashboarding solution. Resources, Gallery Components, bokeh-events.
mercury - Convert Python notebook to web app, Example.
dash - Dashboarding solution by Resources.
visdom - Dashboarding library by facebook.
panel - Dashboarding solution.
altair example - Video.
voila - Turn Jupyter notebooks into standalone web applications.
voila-gridstack - Voila grid layout.


gradio - Create UIs for your machine learning model.

Survey Tools

samplics - Sampling techniques for complex survey designs.

Geographical Tools

folium - Plot geographical maps using the Leaflet.js library, jupyter plugin.
gmaps - Google Maps for Jupyter notebooks.
stadiamaps - Plot geographical maps.
datashader - Draw millions of points on a map.
sklearn - BallTree, Example.
pynndescent - Nearest neighbor descent for approximate nearest neighbors.
geocoder - Geocoding of addresses, IP addresses.
Conversion of different geo formats: talk, repo
geopandas - Tools for geographic data
Low Level Geospatial Tools (GEOS, GDAL/OGR, PROJ.4)
Vector Data (Shapely, Fiona, Pyproj)
Raster Data (Rasterio)
Plotting (Descartes, Catropy)
Predict economic indicators from Open Street Map ipynb.
PySal - Python Spatial Analysis Library.
geography - Extract countries, regions and cities from a URL or text.
cartogram - Distorted maps based on population.

Recommender Systems

Examples: 1, 2, 2-ipynb, 3.
surprise - Recommender, talk.
turicreate - Recommender.
implicit - Fast Collaborative Filtering for Implicit Feedback Datasets.
spotlight - Deep recommender models using PyTorch.
lightfm - Recommendation algorithms for both implicit and explicit feedback.
funk-svd - Fast SVD.
pywFM - Factorization.

Decision Tree Models

Intro to Decision Trees and Random Forests, Intro to Gradient Boosting 1, 2, Decision Tree Visualization
lightgbm - Gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, doc.
xgboost - Gradient boosting (GBDT, GBRT or GBM) library, doc, Methods for CIs: link1, link2.
catboost - Gradient boosting.
h2o - Gradient boosting and general machine learning framework.
snapml - Gradient boosting and general machine learning framework by IBM, for CPU and GPU. PyPI
pycaret - Wrapper for xgboost, lightgbm, catboost etc.
thundergbm - GBDTs and Random Forest.
h2o - Gradient boosting.
forestci - Confidence intervals for random forests.
scikit-garden - Quantile Regression.
grf - Generalized random forest.
dtreeviz - Decision tree visualization and model interpretation.
Nuance - Decision tree visualization.
rfpimp - Feature Importance for RandomForests using Permuation Importance.
Why the default feature importance for random forests is wrong: link
treeinterpreter - Interpreting scikit-learn's decision tree and random forest predictions.
bartpy - Bayesian Additive Regression Trees.
infiniteboost - Combination of RFs and GBDTs.
merf - Mixed Effects Random Forest for Clustering, video
rrcf - Robust Random Cut Forest algorithm for anomaly detection on streams.
groot - Robust decision trees.
linear-tree - Trees with linear models at the leaves.

Natural Language Processing (NLP) / Text Processing

talk-nb, nb2, talk.
Text classification Intro, Preprocessing blog post.
gensim - NLP, doc2vec, word2vec, text processing, topic modelling (LSA, LDA), Example, Coherence Model for evaluation.
Embeddings - GloVe ([1], [2]), StarSpace, wikipedia2vec, visualization.
magnitude - Vector embedding utility package.
pyldavis - Visualization for topic modelling.
spaCy - NLP.
NTLK - NLP, helpful KMeansClusterer with cosine_distance.
pytext - NLP from Facebook.
fastText - Efficient text classification and representation learning.
annoy - Approximate nearest neighbor search.
faiss - Approximate nearest neighbor search.
pysparnn - Approximate nearest neighbor search.
infomap - Cluster (word-)vectors to find topics, example.
datasketch - Probabilistic data structures for large data (MinHash, HyperLogLog).
flair - NLP Framework by Zalando.
stanfordnlp - NLP Library.
Chatistics - Turn Messenger, Hangouts, WhatsApp and Telegram chat logs into DataFrames.
textvec - Supervised text vectorization tool.
textdistance - Collection for comparing distances between two or more sequences.


Search Engine Correlation

Biology / Bioinformatics

Biostatistics / Robust statistics

MinCovDet - Robust estimator of covariance, RMPV, Paper, App1, App2.
winsorize - Simple adjustment of outliers.
moderated z-score - Weighted average of z-scores based on Spearman correlation.


Single cell tutorial.
cellxgene - Interactive explorer for single-cell transcriptomics data.
scanpy - Analyze single-cell gene expression data, tutorial.
besca - Beyond single-cell analysis.
janggu - Deep Learning for Genomics.
gdsctools - Drug responses in the context of the Genomics of Drug Sensitivity in Cancer project, ANOVA, IC50, MoBEM, doc.


See also Microscopy Section above.
Overview over cell segmentation algorithms
python_for_microscopists - Notebooks and associated youtube channel for a variety of image processing tasks.
mahotas - Image processing (Bioinformatics), example.
imagepy - Software package for bioimage analysis.
scimap - Spatial Single-Cell Analysis Toolkit.
CellProfiler - Biological image analysis.
imglyb - Viewer for large images, talk, slides.
microscopium - Unsupervised clustering of images + viewer, talk.
cytokit - Analyzing properties of cells in fluorescent microscopy datasets.
ZeroCostDL4Mic - Deep-Learning in Microscopy.

Drug discovery

TDC - Drug Discovery and Development.
DeepPurpose - Deep Learning Based Molecular Modeling and Prediction Toolkit.


mit6874 - Computational Systems Biology: Deep Learning in the Life Sciences.

Image Processing

cv2 - OpenCV, classical algorithms: Gaussian Filter, Morphological Transformations.
scikit-image - Image processing.

Neural Networks

Convolutional Neural Networks for Visual Recognition - Stanford CS class.
ConvNet Shape Calculator - Calculate output dimensions of Conv2D layer.
Great Gradient Descent Article.
Intro to semi-supervised learning.

Tutorials & Viewer course - Lessons 1-7, Lessons 8-14
Tensorflow without a PhD - Neural Network course by Google.
Feature Visualization: Blog, PPT
Tensorflow Playground
Visualization of optimization algorithms, Another visualization
cutouts-explorer - Image Viewer.

Image Related

imgaug - More sophisticated image preprocessing.
Augmentor - Image augmentation library.
keras preprocessing - Preprocess images.
albumentations - Wrapper around imgaug and other libraries.
augmix - Image augmentation from Google.
kornia - Image augmentation, feature extraction and loss functions.
augly - Image, audio, text, video augmentation from Facebook.

Lossfunction Related

SegLoss - List of loss functions for medical image segmentation.

Activation Functions

rational_activations - Rational activation functions.

Text Related

ktext - Utilities for pre-processing text for deep learning in Keras.
textgenrnn - Ready-to-use LSTM for text generation.
ctrl - Text generation.

Neural network and deep learning frameworks

OpenMMLab - Framework for segmentation, classification and lots of other computer vision tasks.
caffe - Deep learning framework, pretrained models.
mxnet - Deep learning framework, book.

Libs General

keras - Neural Networks on top of tensorflow, examples.
keras-contrib - Keras community contributions.
keras-tuner - Hyperparameter tuning for Keras.
hyperas - Keras + Hyperopt: Convenient hyperparameter optimization wrapper.
elephas - Distributed Deep learning with Keras & Spark.
tflearn - Neural Networks on top of tensorflow.
tensorlayer - Neural Networks on top of tensorflow, tricks.
tensorforce - Tensorflow for applied reinforcement learning.
autokeras - AutoML for deep learning.
PlotNeuralNet - Plot neural networks.
lucid - Neural network interpretability, Activation Maps.
tcav - Interpretability method.
AdaBound - Optimizer that trains as fast as Adam and as good as SGD, alt.
foolbox - Adversarial examples that fool neural networks.
hiddenlayer - Training metrics.
imgclsmob - Pretrained models.
netron - Visualizer for deep learning and machine learning models.
ffcv - Fast dataloder.

Libs Pytorch

Good Pytorch Introduction
skorch - Scikit-learn compatible neural network library that wraps pytorch, talk, slides.
fastai - Neural Networks in pytorch.
timm - Pytorch image models.
ignite - Highlevel library for pytorch.
torchcv - Deep Learning in Computer Vision.
pytorch-optimizer - Collection of optimizers for pytorch.
pytorch-lightning - Wrapper around PyTorch.
lightly - MoCo, SimCLR, SimSiam, Barlow Twins, BYOL, NNCLR.
MONAI - Deep learning in healthcare imaging.
kornia - Image transformations, epipolar geometry, depth estimation.
torchinfo - Nice model summary.
lovely-tensors - Inspect tensors, mean, std, inf values.

Distributed Libs

flexflow - Distributed TensorFlow Keras and PyTorch.
horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

Architecture Visualization

Awesome List.
netron - Viewer for neural networks.
visualkeras - Visualize Keras networks.

Object detection / Instance Segmentation

Good Yolo Explanation
segmentation_models - Segmentation models with pretrained backbones: Unet, FPN, Linknet, PSPNet.
yolact - Fully convolutional model for real-time instance segmentation.
EfficientDet Pytorch, EfficientDet Keras - Scalable and Efficient Object Detection.
detectron2 - Object Detection (Mask R-CNN) by Facebook.
simpledet - Object Detection and Instance Recognition.
CenterNet - Object detection.
FCOS - Fully Convolutional One-Stage Object Detection.
norfair - Real-time 2D object tracking.
Detic - Detector with image classes that can use image-level labels (facebookresearch).
EasyCV - Image segmentation, classification, metric-learning, object detection, pose estimation.

Image Annotation

cvat - Image annotation tool.
pigeon - Create annotations from within a Jupyter notebook.

Image Classification

nfnets - Neural network.
efficientnet - Neural network.
pycls - Pytorch image classification networks: ResNet, ResNeXt, EfficientNet, and RegNet (by Facebook).

Applications and Snippets

SPADE - Semantic Image Synthesis.
Entity Embeddings of Categorical Variables, code, kaggle
Image Super-Resolution - Super-scaling using a Residual Dense Network.
Cell Segmentation - Talk, Blog Posts: 1, 2
deeplearning-models - Deep learning models.

Variational Autoencoders (VAEs)

Variational Autoencoder Explanation Video
disentanglement_lib - BetaVAE, FactorVAE, BetaTCVAE, DIP-VAE.
ladder-vae-pytorch - Ladder Variational Autoencoders (LVAE).
benchmark_VAE - Unifying Generative Autoencoder implementations.

Generative Adversarial Networks (GANs)

Awesome GAN Applications
The GAN Zoo - List of Generative Adversarial Networks.
CycleGAN and Pix2pix - Various image-to-image tasks.
Tensorflow GAN implementations
Pytorch GAN implementations
Pytorch GAN implementations
StudioGAN - Pytorch GAN implementations.


SegFormer - Simple and Efficient Design for Semantic Segmentation with Transformers.
esvit - Efficient self-supervised Vision Transformers.
nystromformer - More efficient transformer because of approximate self-attention.

Deep learning on structured data

Great overview for deep learning for tabular data

Graph-Based Neural Networks

How to do Deep Learning on Graphs with Graph Convolutional Networks
Introduction To Graph Convolutional Networks
An attempt at demystifying graph deep learning
ogb - Open Graph Benchmark, Benchmark datasets.
networkx - Graph library.
cugraph - RAPIDS, Graph library on the GPU.
pytorch-geometric - Various methods for deep learning on graphs.
dgl - Deep Graph Library.
graph_nets - Build graph networks in Tensorflow, by deepmind.

Model conversion

hummingbird - Compile trained ML models into tensor computations (by Microsoft).


cuML - RAPIDS, Run traditional tabular ML tasks on GPUs, Intro.
thundergbm - GBDTs and Random Forest.
thundersvm - Support Vector Machines.
Legate Numpy - Distributed Numpy array multiple using GPUs by Nvidia (not released yet) video.


Understanding SVM Regression: slides, forum, paper

pyearth - Multivariate Adaptive Regression Splines (MARS), tutorial.
pygam - Generalized Additive Models (GAMs), Explanation.
GLRM - Generalized Low Rank Models.
tweedie - Specialized distribution for zero inflated targets, Talk.
MAPIE - Estimating prediction intervals.
Regressio - Regression and Spline models.


orthopy - Orthogonal polynomials in all shapes and sizes.


Talk, Notebook
Blog post: Probability Scoring
All classification metrics
DESlib - Dynamic classifier and ensemble selection.
human-learn - Create and tune classifier based on your rule set.

Metric Learning

Contrastive Representation Learning

metric-learn - Supervised and weakly-supervised metric learning algorithms.
pytorch-metric-learning - Pytorch metric learning.
deep_metric_learning - Methods for deep metric learning.
ivis - Metric learning using siamese neural networks.
tensorflow similarity - Metric learning.

Distance Functions

scipy.spatial - All kinds of distance metrics.
pyemd - Earth Mover's Distance / Wasserstein distance, similarity between histograms. OpenCV implementation, POT implementation
dcor - Distance correlation and related Energy statistics.
GeomLoss - Kernel norms, Hausdorff divergences, Debiased Sinkhorn divergences (=approximation of Wasserstein distance).

Self-supervised Learning

lightly - MoCo, SimCLR, SimSiam, Barlow Twins, BYOL, NNCLR.
vissl - Self-Supervised Learning with PyTorch: RotNet, Jigsaw, NPID, ClusterFit, PIRL, SimCLR, MoCo, DeepCluster, SwAV.


Overview of clustering algorithms applied image data (= Deep Clustering).
Clustering with Deep Learning: Taxonomy and New Methods.
Hierarchical Cluster Analysis (R Tutorial) - Dendrogram, Tanglegram
hdbscan - Clustering algorithm, talk, blog.
pyclustering - All sorts of clustering algorithms.
FCPS - Fundamental Clustering Problems Suite (R package).
GaussianMixture - Generalized k-means clustering using a mixture of Gaussian distributions, video.
nmslib - Similarity search library and toolkit for evaluation of k-NN methods.
buckshotpp - Outlier-resistant and scalable clustering algorithm.
merf - Mixed Effects Random Forest for Clustering, video
tree-SNE - Hierarchical clustering algorithm based on t-SNE.
MiniSom - Pure Python implementation of the Self Organizing Maps.
distribution_clustering, paper, related paper, alt.
phenograph - Clustering by community detection.
FastPG - Clustering of single cell data (RNA). Improvement of phenograph, Paper.
HypHC - Hyperbolic Hierarchical Clustering.
BanditPAM - Improved k-Medoids Clustering.
dendextend - Comparing dendrograms (R package).
DeepDPM - Deep Clustering With An Unknown Number of Clusters.

Clustering Evalutation

Wagner, Wagner - Comparing Clusterings - An Overview

Assessing the quality of a clustering (video)
fpc - Various methods for clustering and cluster validation (R package).

  • Minimum distance between any two clusters
  • Distance between centroids
  • p-separation index: Like minimum distance. Look at the average distance to nearest point in different cluster for p=10% "border" points in any cluster. Measuring density, measuring mountains vs valleys
  • Estimate density by weighted count of close points

Other measures:

  • Within-cluster average distance
  • Mean of within-cluster average distance over nearest-cluster average distance (silhouette score)
  • Within-cluster similarity measure to normal/uniform
  • Within-cluster (squared) distance to centroid (this is the k-Means loss function)
  • Correlation coefficient between distance we originally had to the distance the are induced by the clustering (Huberts Gamma)
  • Entropy of cluster sizes
  • Average largest within-cluster gap
  • Variation of clusterings on bootstrapped data

Multi-label classification

scikit-multilearn - Multi-label classification, talk.

Signal Processing and Filtering

Stanford Lecture Series on Fourier Transformation, Youtube, Lecture Notes.
Visual fourier explanation.
The Scientist & Engineer's Guide to Digital Signal Processing (1999).
Kalman Filter article.
Kalman Filter book - Focuses on intuition using Jupyter Notebooks. Includes Baysian and various Kalman filters.
Interactive Tool for FIR and IIR filters, Examples.
filterpy - Kalman filtering and optimal estimation library.


geomstats - Computations and statistics on manifolds with geometric structures.

Time Series

statsmodels - Time series analysis, seasonal decompose example, SARIMA, granger causality.
kats - Time series prediction library by Facebook.
prophet - Time series prediction library by Facebook.
neural_prophet - Time series prediction built on Pytorch.
pyramid, pmdarima - Wrapper for (Auto-) ARIMA.
modeltime - Time series forecasting framework (R package).
pyflux - Time series prediction algorithms (ARIMA, GARCH, GAS, Bayesian).
atspy - Automated Time Series Models.
pm-prophet - Time series prediction and decomposition library.
htsprophet - Hierarchical Time Series Forecasting using Prophet.
nupic - Hierarchical Temporal Memory (HTM) for Time Series Prediction and Anomaly Detection.
tensorflow - LSTM and others, examples: link, link, link, Explain LSTM, seq2seq: 1, 2, 3, 4
tspreprocess - Preprocessing: Denoising, Compression, Resampling.
tsfresh - Time series feature engineering.
tsfel - Time series feature extraction.
thunder - Data structures and algorithms for loading, processing, and analyzing time series data.
gatspy - General tools for Astronomical Time Series, talk.
gendis - shapelets, example.
tslearn - Time series clustering and classification, TimeSeriesKMeans, TimeSeriesKMeans.
pastas - Simulation of time series.
fastdtw - Dynamic Time Warp Distance.
fable - Time Series Forecasting (R package).
pydlm - Bayesian time series modeling (R package, Blog post)
PyAF - Automatic Time Series Forecasting.
luminol - Anomaly Detection and Correlation library from Linkedin.
matrixprofile-ts - Detecting patterns and anomalies, website, ppt, alternative.
stumpy - Another matrix profile library.
obspy - Seismology package. Useful classic_sta_lta function.
RobustSTL - Robust Seasonal-Trend Decomposition.
seglearn - Time Series library.
pyts - Time series transformation and classification, Imaging time series.
Turn time series into images and use Neural Nets: example, example.
sktime, sktime-dl - Toolbox for (deep) learning with time series.
adtk - Time Series Anomaly Detection.
rocket - Time Series classification using random convolutional kernels.
luminaire - Anomaly Detection for time series.
etna - Time Series library.
Chaos Genius - ML powered analytics engine for outlier/anomaly detection and root cause analysis.

Time Series Evaluation

TimeSeriesSplit - Sklearn time series split.
tscv - Evaluation with gap.

Financial Data and Trading

Tutorial on using cvxpy: 1, 2
pandas-datareader - Read stock data.
yfinance - Read stock data from Yahoo Finance.
findatapy - Read stock data from various sources.
ta - Technical analysis library.
backtrader - Backtesting for trading strategies.
surpriver - Find high moving stocks before they move using anomaly detection and machine learning.
ffn - Financial functions.
bt - Backtesting algorithms.
alpaca-trade-api-python - Commission-free trading through API.
eiten - Eigen portfolios, minimum variance portfolios and other algorithmic investing strategies.
tf-quant-finance - Quantitative finance tools in tensorflow, by Google.
quantstats - Portfolio management.
Riskfolio-Lib - Portfolio optimization and strategic asset allocation.
OpenBBTerminal - Terminal.
mplfinance - Financial markets data visualization.

Quantopian Stack

pyfolio - Portfolio and risk analytics.
zipline - Algorithmic trading.
alphalens - Performance analysis of predictive stock factors.
empyrical - Financial risk metrics.
trading_calendars - Calendars for various securities exchanges.

Survival Analysis

Time-dependent Cox Model in R.
lifelines - Survival analysis, Cox PH Regression, talk, talk2.
scikit-survival - Survival analysis.
xgboost - "objective": "survival:cox" NHANES example
survivalstan - Survival analysis, intro.
convoys - Analyze time lagged conversions.
RandomSurvivalForests (R packages: randomForestSRC, ggRandomForests).
pysurvival - Survival analysis.
DeepSurvivalMachines - Fully Parametric Survival Regression.
auton-survival - Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Events.

Outlier Detection & Anomaly Detection

sklearn - Isolation Forest and others.
pyod - Outlier Detection / Anomaly Detection.
eif - Extended Isolation Forest.
AnomalyDetection - Anomaly detection (R package).
luminol - Anomaly Detection and Correlation library from Linkedin.
Distances for comparing histograms and detecting outliers - Talk: Kolmogorov-Smirnov, Wasserstein, Energy Distance (Cramer), Kullback-Leibler divergence.
banpei - Anomaly detection library based on singular spectrum transformation.
telemanom - Detect anomalies in multivariate time series data using LSTMs.
luminaire - Anomaly Detection for time series.

Concept Drift & Domain Shift

TorchDrift - Drift Detection for PyTorch Models.
alibi-detect - Algorithms for outlier, adversarial and drift detection.
evidently - Evaluate and monitor ML models from validation to production.
Lipton et al. - Detecting and Correcting for Label Shift with Black Box Predictors.
Bu et al. - A pdf-Free Change Detection Test Based on Density Difference Estimation.


lightning - Large-scale linear classification, regression and ranking.


SLIM - Scoring systems for classification, Supersparse linear integer models.

Causal Inference

CS 594 Causal Inference and Learning
Statistical Rethinking - Video Lecture Series, Bayesian Statistics, Causal Models, R, python, numpyro1, numpyro2, tensorflow-probability.
Python Causality Handbook
dowhy - Estimate causal effects.
CausalImpact - Causal Impact Analysis (R package).
causallib - Modular causal inference analysis and model evaluations by IBM, examples.
causalml - Causal inference by Uber.
upliftml - Causal inference by
EconML - Heterogeneous Treatment Effects Estimation by Microsoft.
causality - Causal analysis using observational datasets.
DoubleML - Machine Learning + Causal inference, Tweet, Presentation, Paper.


Bours - Confounding
Bours - Effect Modification and Interaction

Probabilistic Modeling and Bayes

Intro, Guide
PyMC3 - Bayesian modelling, intro
numpyro - Probabilistic programming with numpy, built on pyro.
pomegranate - Probabilistic modelling, talk.
pmlearn - Probabilistic machine learning.
arviz - Exploratory analysis of Bayesian models.
zhusuan - Bayesian deep learning, generative models.
edward - Probabilistic modeling, inference, and criticism, Mixture Density Networks (MNDs), MDN Explanation.
Pyro - Deep Universal Probabilistic Programming.
tensorflow probability - Deep learning and probabilistic modelling, talk1, notebook talk1, talk2, example.
bambi - High-level Bayesian model-building interface on top of PyMC3.
neural-tangents - Infinite Neural Networks.
bnlearn - Bayesian networks, parameter learning, inference and sampling methods.

Gaussian Processes

Visualization, Article
GPyOpt - Gaussian process optimization.
GPflow - Gaussian processes (Tensorflow).
gpytorch - Gaussian processes (Pytorch).

Stacking Models and Ensembles

Model Stacking Blog Post
mlxtend - EnsembleVoteClassifier, StackingRegressor, StackingCVRegressor for model stacking.
vecstack - Stacking ML models.
StackNet - Stacking ML models.
mlens - Ensemble learning.
combo - Combining ML models (stacking, ensembling).

Model Evaluation

pycm - Multi-class confusion matrix.
pandas_ml - Confusion matrix.
Plotting learning curve: link.
yellowbrick - Learning curve.
pyroc - Receiver Operating Characteristic (ROC) curves.

Model Uncertainty

awesome-conformal-prediction - Uncertainty quantification.
uncertainty-toolbox - Predictive uncertainty quantification, calibration, metrics, and visualization.

Interpretable Classifiers and Regressors

skope-rules - Interpretable classifier, IF-THEN rules.
sklearn-expertsys - Interpretable classifiers, Bayesian Rule List classifier.

Model Explanation, Interpretability, Feature Importance

Princeton - Reproducibility Crisis in ML‑based Science
Book, Examples
shap - Explain predictions of machine learning models, talk, Good Shap intro.
treeinterpreter - Interpreting scikit-learn's decision tree and random forest predictions.
lime - Explaining the predictions of any machine learning classifier, talk, Warning (Myth 7).
lime_xgboost - Create LIMEs for XGBoost.
eli5 - Inspecting machine learning classifiers and explaining their predictions.
lofo-importance - Leave One Feature Out Importance, talk, examples: 1, 2, 3.
pybreakdown - Generate feature contribution plots.
pycebox - Individual Conditional Expectation Plot Toolbox.
pdpbox - Partial dependence plot toolbox, example.
partial_dependence - Visualize and cluster partial dependence.
skater - Unified framework to enable model interpretation.
anchor - High-Precision Model-Agnostic Explanations for classifiers.
l2x - Instancewise feature selection as methodology for model interpretation.
contrastive_explanation - Contrastive explanations.
DrWhy - Collection of tools for explainable AI.
lucid - Neural network interpretability.
xai - An eXplainability toolbox for machine learning.
innvestigate - A toolbox to investigate neural network predictions.
dalex - Explanations for ML models (R package).
interpretml - Fit interpretable models, explain models.
shapash - Model interpretability.
imodels - Interpretable ML package.
captum - Model interpretability and understanding for PyTorch.

Automated Machine Learning

AdaNet - Automated machine learning based on tensorflow.
tpot - Automated machine learning tool, optimizes machine learning pipelines.
auto_ml - Automated machine learning for analytics & production.
autokeras - AutoML for deep learning.
nni - Toolkit for neural architecture search and hyper-parameter tuning by Microsoft.
automl-gs - Automated machine learning.
mljar - Automated machine learning.
automl_zero - Automatically discover computer programs that can solve machine learning tasks from Google.
AlphaPy - Automated Machine Learning using scikit-learn xgboost, LightGBM and others.

Graph Representation Learning

Karate Club - Unsupervised learning on graphs.
Pytorch Geometric - Graph representation learning with PyTorch.
DLG - Graph representation learning with TensorFlow.

Convex optimization

cvxpy - Modeling language for convex optimization problems. Tutorial: 1, 2

Evolutionary Algorithms & Optimization

deap - Evolutionary computation framework (Genetic Algorithm, Evolution strategies).
evol - DSL for composable evolutionary algorithms, talk.
platypus - Multiobjective optimization.
autograd - Efficiently computes derivatives of numpy code.
nevergrad - Derivation-free optimization.
gplearn - Sklearn-like interface for genetic programming.
blackbox - Optimization of expensive black-box functions.
Optometrist algorithm - paper.
DeepSwarm - Neural architecture search.
evotorch - Evolutionary computation library built on Pytorch.

Hyperparameter Tuning

sklearn - GridSearchCV, RandomizedSearchCV.
sklearn-deap - Hyperparameter search using genetic algorithms.
hyperopt - Hyperparameter optimization.
hyperopt-sklearn - Hyperopt + sklearn.
optuna - Hyperparamter optimization, Talk.
skopt - BayesSearchCV for Hyperparameter search.
tune - Hyperparameter search with a focus on deep learning and deep reinforcement learning.
hypergraph - Global optimization methods and hyperparameter optimization.
bbopt - Black box hyperparameter optimization.
dragonfly - Scalable Bayesian optimisation.
botorch - Bayesian optimization in PyTorch.
ax - Adaptive Experimentation Platform by Facebook.
lightning-hpo - Hyperparameter optimization based on optuna.

Incremental Learning, Online Learning

sklearn - PassiveAggressiveClassifier, PassiveAggressiveRegressor.
river - Online machine learning.
Kaggler - Online Learning algorithms.
onelearn - Online Random Forests.

Active Learning

modAL - Active learning framework.

Reinforcement Learning

YouTube, YouTube
Intro to Monte Carlo Tree Search (MCTS) - 1, 2, 3
AlphaZero methodology - 1, 2, 3, Cheat Sheet
RLLib - Library for reinforcement learning.
Horizon - Facebook RL framework.

Deployment and Lifecycle Management

Workflow Scheduling and Orchestration

airflow - Schedule and monitor workflows.
prefect - Python specific workflow scheduling.
dagster - Development, production and observation of data assets.
ploomber - Workflow orchestration.
kestra - Workflow orchestration.
cml - CI/CD for Machine Learning Projects.
rocketry - Task scheduling.

Containerization and Docker

Reduce size of docker images (video)
Optimize Docker Image Size
cog - Facilitates building Docker images.

Dependency Management

dephell - Dependency management.
poetry - Dependency management.
pyup - Dependency management.
pypi-timemachine - Install packages with pip as if you were in the past.

Data Versioning, Databases, Pipelines and Model Serving

dvc - Version control for large files.
hangar - Version control for tensor data.
kedro - Build data pipelines.
feast - Feature store. Video.
pinecone - Database for vector search applications.
truss - Serve ML models.
milvus - Vector database for similarity search.
mlem - Version and deploy your ML models following GitOps principles.

Data Science Related

m2cgen - Transpile trained ML models into other languages.
sklearn-porter - Transpile trained scikit-learn estimators to C, Java, JavaScript and others.
mlflow - Manage the machine learning lifecycle, including experimentation, reproducibility and deployment.
modelchimp - Experiment Tracking.
skll - Command-line utilities to make it easier to run machine learning experiments.
BentoML - Package and deploy machine learning models for serving in production.
dagster - Tool with focus on dependency graphs.
knockknock - Be notified when your training ends.
metaflow - Lifecycle Management Tool by Netflix.
cortex - Deploy machine learning models.
Neptune - Experiment tracking and model registry.
clearml - Experiment Manager, MLOps and Data-Management.
polyaxon - MLOps.
sematic - Deploy machine learning models.
zenml - MLOPs.

Math and Background

All kinds of math and statistics resources
Gilbert Strang - Linear Algebra
Gilbert Strang - Matrix Methods in Data Analysis, Signal Processing, and Machine Learning


daft - Render probabilistic graphical models using matplotlib.
unyt - Working with units.
scrapy - Web scraping library.
VowpalWabbit - ML Toolkit from Microsoft.
Python Record Linkage Toolkit - link records in or between data sources.

General Python Programming

more_itertools - Extension of itertools.
funcy - Fancy and practical functional tools.
dateparser - A better date parser.
jellyfish - Approximate string matching.
coloredlogs - Colored logging output.

Resources - Blog.
Machine Learning Videos
Data Science Notebooks
Recommender Systems (Microsoft)
Datascience Cheatsheets


datasharing - Guide to data sharing.


Chan - Introduction to Probability for Data Science
Colonescu - Principles of Econometrics with R

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NYU Deep Learning SP21 - Youtube Playlist.

Things I google a lot

Color codes
Frequency codes for time series
Date parsing codes
Feature Calculators tsfresh


Do you know a package that should be on this list? Did you spot a package that is no longer maintained and should be removed from this list? Then feel free to read the contribution guidelines and submit your pull request or create a new issue.



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