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, intelex.
matplotlib - Plotting library.
seaborn - Data visualization library based on matplotlib.
ydata-profiling - Descriptive statistics using ProfileReport.
sklearn_pandas - Helpful DataFrameMapper class.
missingno - Missing data visualization.
rainbow-csv - VSCode plugin to display .csv files with nice colors.
Python Best Practices Guide
pyenv - Manage multiple Python versions on your system.
poetry - Dependency management.
pyscaffold - Python project template generator.
hydra - Configuration management.
hatch - Python project management.
more_itertools - Extension of itertools.
tqdm - Progress bars for for-loops. Also supports pandas apply().
loguru - Python logging.
pandasvault - Large collection of pandas tricks.
polars - Multi-threaded alternative to pandas.
xarray - Extends pandas to n-dimensional arrays.
mlx - An array framework for Apple silicon.
pandas_flavor - Write custom accessors like .str and .dt.
duckdb - Efficiently run SQL queries on pandas DataFrame.
modin - Parallelization library for faster pandas DataFrame.
vaex - Out-of-Core DataFrames.
pandarallel - Parallelize pandas operations.
swifter - Apply any function to a pandas DataFrame faster.
Jupyter Tricks
ipyflow - IPython kernel for Jupyter with additional features.
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.
lux - DataFrame visualization within Jupyter.
pandasgui - GUI for viewing, plotting and analyzing Pandas DataFrames.
dtale - View and analyze Pandas data structures, integrating with Jupyter.
itables - Interactive tables in Jupyter.
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.
textract - Extract text from any document.
spark - DataFrame for big data, cheatsheet, tutorial.
dask, dask-ml - Pandas DataFrame for big data and machine learning library, resources, talk1, talk2, notebooks, videos.
h2o - Helpful H2OFrame class for out-of-memory dataframes.
datatable - Data Table for big data support.
cuDF - GPU DataFrame Library, Intro.
cupy - NumPy-like API accelerated with CUDA.
ray - Flexible, high-performance distributed execution framework.
bottleneck - Fast NumPy array functions written in C.
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).
csvkit - Command line tool for CSV files.
csvsort - Sort large csv files.
The ASA Statement on p-Values: Context, Process, and Purpose
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
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
Estimating Effect Sizes From Pretest-Posttest-Control Group Designs - Scott B. Morris, Twitter
test_proportions_2indep - Proportion test.
G-Test - Alternative to chi-square test, power_divergence.
torch-two-sample - Friedman-Rafsky Test: Compare two population based on a multivariate generalization of the Runstest. Explanation, Application
Sequential Analysis - Wikipedia.
sequential - Exact Sequential Analysis for Poisson and Binomial Data (R package).
confseq - Uniform boundaries, confidence sequences, and always-valid p-values.
Friends don't let friends make certain types of data visualization
Great Overview over Visualizations
Dependent Propabilities
Null Hypothesis Significance Testing (NHST) and Sample Size Calculation
Correlation
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
Statistical Power and Sample Size Calculation Tools
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
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
Same Stats, Different Graphs: Generating Datasets with Varied Appearance and Identical Statistics through Simulated Annealing, Youtube
How large is that number in the Law of Large Numbers?
The Prosecutor's Fallacy
The Dunning-Kruger Effect is Autocorrelation
Rafi, Greenland - Semantic and cognitive tools to aid statistical science: replace confidence and significance by compatibility and surprise
Collins et al. - Evaluation of clinical prediction models (part 1): from development to external validation - Twitter
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).
quartets - Anscombe’s Quartet, Causal Quartet, Datasaurus Dozen and others (R package).
Checklist.
pyjanitor - Clean messy column names.
skimpy - Create summary statistics of dataframes. Helpful clean_columns() function.
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))
cleanlab - Machine learning with noisy labels, finding mislabelled data, and uncertainty quantification. Also see awesome list below.
doubtlab - Find bad or noisy labels.
iterative-stratification - Stratification of multilabel data.
Vincent Warmerdam: Untitled12.ipynb - Using df.pipe()
Vincent Warmerdam: Winning with Simple, even Linear, Models
sklearn - Pipeline, examples.
pdpipe - Pipelines for DataFrames.
scikit-lego - Custom transformers for pipelines.
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.
temporian - Time series feature engineering by Google.
pypeln - Concurrent data pipelines.
feature-engine - Encoders, transformers, etc.
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.
apricot - Selecting subsets of data sets to train machine learning models quickly.
ducks - Index data for fast lookup by any combination of fields.
Check also the Clustering section and self-supervised learning section for ideas!
Review
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
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).
Phantom oscillations in PCA.
What to use instead of PCA.
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.
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).
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.
jupyter-scatter - Interactive 2D scatter plot widget for Jupyter.
palettable - Color palettes from colorbrewer2.
colorcet - Collection of perceptually uniform colormaps.
Named Colors Wheel - Color wheel for all named HTML colors.
py-shiny - Shiny for Python, talk.
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 plot.ly. 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.
samplics - Sampling techniques for complex survey designs.
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.
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.
PySal - Python Spatial Analysis Library.
geography - Extract countries, regions and cities from a URL or text.
cartogram - Distorted maps based on population.
Examples: 1, 2, 2-ipynb, 3.
surprise - Recommender, talk.
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.
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.
pycaret - Wrapper for xgboost, lightgbm, catboost etc.
forestci - Confidence intervals for random forests.
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
bartpy - Bayesian Additive Regression Trees.
merf - Mixed Effects Random Forest for Clustering, video
groot - Robust decision trees.
linear-tree - Trees with linear models at the leaves.
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.
datasketch - Probabilistic data structures for large data (MinHash, HyperLogLog).
flair - NLP Framework by Zalando.
stanza - NLP Library.
Chatistics - Turn Messenger, Hangouts, WhatsApp and Telegram chat logs into DataFrames.
textdistance - Collection for comparing distances between two or more sequences.
MIT 7.016 Introductory Biology, Fall 2018 - Videos 27, 28, and 29 talk about staining and imaging.
bioimaging.org - A biologists guide to planning and performing quantitative bioimaging experiments.
Bio-image Analysis Notebooks - Large collection of image processing workflows, including point-spread-function estimation and deconvolution, 3D cell segmentation, feature extraction using pyclesperanto and others.
python_for_microscopists - Notebooks and associated youtube channel for a variety of image processing tasks.
jump-cellpainting - Cellpainting dataset.
MedMNIST - Datasets for 2D and 3D Biomedical Image Classification.
CytoImageNet - Huge diverse dataset like ImageNet but for cell images.
Haghighi - Gene Expression and Morphology Profiles.
broadinstitute/lincs-profiling-complementarity - Cellpainting vs. L1000 assay.
MinCovDet - Robust estimator of covariance, RMPV, Paper, App1, App2.
moderated z-score - Weighted average of z-scores based on Spearman correlation.
winsorize - Simple adjustment of outliers.
Zhang XHD (2008) - Novel analytic criteria and effective plate designs for quality control in genome-wide RNAi screens
Iversen - A Comparison of Assay Performance Measures in Screening Assays, Signal Window, Z′ Factor, and Assay Variability Ratio
Z-factor - Measure of statistical effect size.
Z'-factor - Measure of statistical effect size.
CV - Coefficient of variation.
SSMD - Strictly standardized mean difference.
Signal Window - Assay quality measurement.
BD Spectrum Viewer - Calculate spectral overlap, bleed through for fluorescence microscopy dyes.
SpectraViewer - Visualize the spectral compatibility of fluorophores (PerkinElmer).
Thermofisher Spectrum Viewer - Thermofisher Spectrum Viewer.
Microscopy Resolution Calculator - Calculate resolution of images (Nikon).
PlateEditor - Drug Layout for plates, app, zip, paper.
OME-Zarr - paper, standard
bioformats2raw - Various formats to zarr.
raw2ometiff - Zarr to tiff.
BatchConvert - Wrapper for bioformats2raw to parallelize conversions with nextflow, video.
REMBI model - Recommended Metadata for Biological Images, BioImage Archive: Study Component Guidance, File List Guide, paper, video, spreadsheet
anndata - annotated data matrices in memory and on disk, Docs.
muon - Multimodal omics framework.
mudata - Multimodal Data (.h5mu) implementation.
bdz - Zarr-based format for storing quantitative biological dynamics data.
napari - Image viewer and image processing tool.
Fiji - General purpose tool. Image viewer and image processing tool.
vizarr - Browser-based image viewer for zarr format.
avivator - Browser-based image viewer for tiff files.
OMERO - Image viewer for high-content screening. IDR uses OMERO. Intro
fiftyone - Viewer and tool for building high-quality datasets and computer vision models.
Image Data Explorer - Microscopy Image Viewer, Shiny App, Video.
ImSwitch - Microscopy Image Viewer, Doc, Video.
pixmi - Web-based image annotation and classification tool, App.
DeepCell Label - Data labeling tool to segment images, Video.
napari-sam - Segment Anything Plugin.
napari-chatgpt - ChatGPT Plugin.
aydin - Image denoising.
DivNoising - Unsupervised denoising method.
CSBDeep - Content-aware image restoration, Project page.
skimage - Illumination correction (CLAHE).
cidre - Illumination correction method for optical microscopy.
BaSiCPy - Background and Shading Correction of Optical Microscopy Images, BaSiC.
PICASSO - Blind unmixing without reference spectra measurement, Paper
cytoflow - Flow cytometry. Includes Bleedthrough correction methods.
Linear unmixing in Fiji for Bleedthrough Correction - Youtube.
Bleedthrough Correction using Lumos and Fiji - Link.
AutoUnmix - Link.
CellProfiler, CellProfilerAnalyst - Create image analysis pipelines.
fractal - Framework to process high-content imaging data from UZH, Github.
atomai - Deep and Machine Learning for Microscopy.
py-clesperanto - Tools for 3D microscopy analysis, deskewing and lots of other tutorials, interacts with napari.
qupath - Image analysis.
Labsyspharm Stack see below.
BiaPy - Bioimage analysis pipelines.
SCIP - Image processing pipeline on top of Dask.
DeepCell Kiosk - Image analysis platform.
IMCWorkflow - Image analysis pipeline using steinbock, Twitter, Paper, workflow.
mcmicro - Multiple-choice microscopy pipeline, Website, Paper.
MCQuant - Quantification of cell features.
cylinter - Quality assurance for microscopy images, Website.
ashlar - Whole-slide microscopy image stitching and registration.
scimap - Spatial Single-Cell Analysis Toolkit.
microscopy-tree - Review of cell segmentation algorithms, Paper.
Review of organoid pipelines - Paper.
BioImage.IO - BioImage Model Zoo.
MEDIAR - Cell segmentation.
cellpose - Cell segmentation. Paper, Dataset.
stardist - Cell segmentation with Star-convex Shapes.
UnMicst - Identifying Cells and Segmenting Tissue.
ilastik - Segment, classify, track and count cells. ImageJ Plugin.
nnUnet - 3D biomedical image segmentation.
allencell - Tools for 3D segmentation, classical and deep learning methods.
Cell-ACDC - Python GUI for cell segmentation and tracking.
ZeroCostDL4Mic - Deep-Learning in Microscopy.
DL4MicEverywhere - Bringing the ZeroCostDL4Mic experience using Docker.
EmbedSeg - Embedding-based Instance Segmentation.
segment-anything - Segment Anything (SAM) from Facebook.
micro-sam - Segment Anything for Microscopy.
Segment-Everything-Everywhere-All-At-Once - Segment Everything Everywhere All at Once from Microsoft.
deepcell-tf - Cell segmentation, DeepCell.
labkit - Fiji plugin for image segmentation.
cellpose - Cell images.
omnipose - Cell images.
LIVECell - Cell images.
Sartorius - Neurons.
EmbedSeg - 2D + 3D images.
connectomics - Annotation of the EPFL Hippocampus dataset.
ZeroCostDL4Mic - Stardist example training and test dataset.
seg-eval - Cell segmentation performance evaluation without Ground Truth labels, Paper.
Computer vision challenges in drug discovery - Maciej Hermanowicz
CellProfiler - Biological image analysis.
scikit-image - Image processing.
scikit-image regionprops - Regionprops: area, eccentricity, extent.
mahotas - Zernike, Haralick, LBP, and TAS features, example.
pyradiomics - Radiomics features from medical imaging.
pyefd - Elliptical feature descriptor, approximating a contour with a Fourier series.
pyvips - Faster image processing operations.
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, R package.
nimfa - Nonnegative matrix factorization.
scgen - Batch removal. Doc.
CORAL - Correcting for Batch Effects Using Wasserstein Distance, Code, Paper.
adapt - Awesome Domain Adaptation Python Toolbox.
pytorch-adapt - Various neural network models for domain adaptation.
Single cell tutorial.
PyDESeq2 - Analyzing RNA-seq data.
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.
monkeybread - Analysis of single-cell spatial transcriptomics data.
TDC - Drug Discovery and Development.
DeepPurpose - Deep Learning Based Molecular Modelling and Prediction Toolkit.
Convolutional Neural Networks for Visual Recognition - Stanford CS class.
mit6874 - Computational Systems Biology: Deep Learning in the Life Sciences.
ConvNet Shape Calculator - Calculate output dimensions of Conv2D layer.
Great Gradient Descent Article.
Intro to semi-supervised learning.
fast.ai course - Practical Deep Learning for Coders.
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.
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.
pyvips - Faster image processing operations.
SegLoss - List of loss functions for medical image segmentation.
rational_activations - Rational activation functions.
ktext - Utilities for pre-processing text for deep learning in Keras.
textgenrnn - Ready-to-use LSTM for text generation.
ctrl - Text generation.
OpenMMLab - Framework for segmentation, classification and lots of other computer vision tasks.
caffe - Deep learning framework, pretrained models.
mxnet - Deep learning framework, book.
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 dataloader.
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.
flexflow - Distributed TensorFlow Keras and PyTorch.
horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Awesome List.
netron - Viewer for neural networks.
visualkeras - Visualize Keras networks.
Metrics reloaded: Recommendations for image analysis validation - Guide for choosing correct image analysis metrics, Code, Twitter Thread
Good Yolo Explanation
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.
nfnets - Neural network.
efficientnet - Neural network.
pycls - PyTorch image classification networks: ResNet, ResNeXt, EfficientNet, and RegNet (by Facebook).
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 Autoencoder Explanation Video
disentanglement_lib - BetaVAE, FactorVAE, BetaTCVAE, DIP-VAE.
ladder-vae-pytorch - Ladder Variational Autoencoders (LVAE).
benchmark_VAE - Unifying Generative Autoencoder implementations.
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.
Great overview for deep learning for tabular data
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.
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.
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.
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).
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.
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.
Wagner, Wagner - Comparing Clusterings - An Overview
- Adjusted Rand Index
- Normalized Mutual Information
- Adjusted Mutual Information
- Fowlkes-Mallows Score
- Silhouette Coefficient
- Variation of Information, Julia
- Pair Confusion Matrix
- Consensus Score - The similarity of two sets of biclusters.
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
scikit-multilearn - Multi-label classification, talk.
Stanford Lecture Series on Fourier Transformation, Youtube, Lecture Notes.
Visual Fourier explanation.
The Scientist & Engineer's Guide to Digital Signal Processing (1999) - Chapter 3 has good introduction to Bessel, Butterworth and Chebyshev filters.
Kalman Filter article.
Kalman Filter book - Focuses on intuition using Jupyter Notebooks. Includes Bayesian and various Kalman filters.
Interactive Tool for FIR and IIR filters, Examples.
filterpy - Kalman filtering and optimal estimation library.
- Butterworth low-pass filter example
- Savitzky–Golay filter, W
pandas.Series.rolling - Choose appropriatewin_type.
geomstats - Computations and statistics on manifolds with geometric structures.
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, 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 - Analysis of Groundwater Time Series.
fastdtw - Dynamic Time Warp Distance.
fable - Time Series Forecasting (R package).
pydlm - Bayesian time series modelling (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.
TimeSeriesSplit - Sklearn time series split.
tscv - Evaluation with gap.
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.
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.
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.
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.
rrcf - Robust Random Cut Forest algorithm for anomaly detection on streams.
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.
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 Booking.com.
causality - Causal analysis using observational datasets.
DoubleML - Machine Learning + Causal inference, Tweet, Presentation, Paper.
EconML - Heterogeneous Treatment Effects Estimation by Microsoft.
Bours - Confounding
Bours - Effect Modification and Interaction
Intro, Guide
PyMC3 - Bayesian modelling.
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 modelling, 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.
Visualization, Article
GPyOpt - Gaussian process optimization.
GPflow - Gaussian processes (TensorFlow).
gpytorch - Gaussian processes (PyTorch).
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).
evaluate - Evaluate machine learning models (huggingface).
pycm - Multi-class confusion matrix.
pandas_ml - Confusion matrix.
Plotting learning curve: link.
yellowbrick - Learning curve.
pyroc - Receiver Operating Characteristic (ROC) curves.
awesome-conformal-prediction - Uncertainty quantification.
uncertainty-toolbox - Predictive uncertainty quantification, calibration, metrics, and visualization.
Princeton - Reproducibility Crisis in ML‑based Science
Book, Examples
scikit-learn - Permutation Importance (can be used on any trained classifier) and Partial Dependence
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.
pybreakdown - Generate feature contribution plots.
pycebox - Individual Conditional Expectation Plot Toolbox.
pdpbox - Partial dependence plot toolbox, example.
partial_dependence - Visualize and cluster partial dependence.
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.
AdaNet - Automated machine learning based on TensorFlow.
tpot - Automated machine learning tool, optimizes machine learning pipelines.
autokeras - AutoML for deep learning.
nni - Toolkit for neural architecture search and hyper-parameter tuning by Microsoft.
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.
Karate Club - Unsupervised learning on graphs.
PyTorch Geometric - Graph representation learning with PyTorch.
DLG - Graph representation learning with TensorFlow.
cvxpy - Modelling language for convex optimization problems. Tutorial: 1, 2
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.
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.
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.
sklearn - PassiveAggressiveClassifier, PassiveAggressiveRegressor.
river - Online machine learning.
Kaggler - Online Learning algorithms.
Talk
modAL - Active learning framework.
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.
nextflow - Run scripts and workflow graphs in Docker image using Google Life Sciences, AWS Batch, Website.
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.
huey - Task queue.
Reduce size of docker images (video)
Optimize Docker Image Size
cog - Facilitates building Docker images.
dvc - Version control for large files.
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.
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.
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.
All kinds of math and statistics resources
Gilbert Strang - Linear Algebra
Gilbert Strang - Matrix Methods in Data Analysis, Signal Processing, and Machine Learning
Distill.pub - Blog.
Machine Learning Videos
Data Science Notebooks
Recommender Systems (Microsoft)
Datascience Cheatsheets
datasharing - Guide to data sharing.
Blum - Foundations of Data Science
Chan - Introduction to Probability for Data Science
Colonescu - Principles of Econometrics with R
Awesome Adversarial Machine Learning
Awesome AI Booksmarks
Awesome AI on Kubernetes
Awesome Big Data
Awesome Biological Image Analysis
Awesome Business Machine Learning
Awesome Causality
Awesome Community Detection
Awesome CSV
Awesome Cytodata
Awesome Data Science with Ruby
Awesome Dash
Awesome Decision Trees
Awesome Deep Learning
Awesome ETL
Awesome Financial Machine Learning
Awesome Fraud Detection
Awesome GAN Applications
Awesome Graph Classification
Awesome Industry Machine Learning
Awesome Gradient Boosting
Awesome Learning with Label Noise
Awesome Machine Learning
Awesome Machine Learning Books
Awesome Machine Learning Interpretability
Awesome Machine Learning Operations
Awesome Monte Carlo Tree Search
Awesome Neural Network Visualization
Awesome Online Machine Learning
Awesome Pipeline
Awesome Public APIs
Awesome Python
Awesome Python Data Science
Awesome Python Data Science
Awesome Pytorch
Awesome Quantitative Finance
Awesome Recommender Systems
Awesome Satellite Benchmark Datasets
Awesome Satellite Image for Deep Learning
Awesome Single Cell
Awesome Semantic Segmentation
Awesome Sentence Embedding
Awesome Time Series
Awesome Time Series Anomaly Detection
Awesome Visual Attentions
Awesome Visual Transformer
NYU Deep Learning SP21 - YouTube Playlist.
Color Codes
Frequency codes for time series
Date parsing codes
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.
