r0f1/datascience

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.

Core

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.

General Python Programming

Advanced Python Features - Generics, Protocols, Structural Pattern Matching and more.
uv - Dependency management.
pdm - For large binary distributions, works with uv.
just - Command runner. Replacement for make.
python-dotenv - Manage environment variables.
structlog - Python logging.
more_itertools - Extension of itertools.
tqdm - Progress bars for for-loops. Also supports pandas apply().
hydra - Configuration management.
ruff - Extremely fast Python linter and code formatter, replaces flake8, black, and isort.

Pandas Tricks, Alternatives and Additions

duckdb - Efficiently run SQL queries on pandas DataFrame, duckplyr for R, Great Intro.
ducklake - Duckdb extention for storing data in a datalake.
fireducks - Speedier alternative to pandas with similar API.
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.
daft - Distributed DataFrame.
vaex - Out-of-Core DataFrames.
modin - Parallelization library for faster pandas DataFrame.
swifter - Apply any function to a pandas DataFrame faster (works with modin).
narwhals - Write dataframe-agnostic code compatible with pandas, polars, cuDF, and more.

Tables

great-tables - Display tabular data nicely.

Interactive Dataframe Visualization

pygwalker - Interactive dataframe.
marimo - Visualization and reproducible environment.
lux - DataFrame visualization within Jupyter.
dtale - View and analyze Pandas data structures, integrating with Jupyter.
pandasgui - GUI for viewing, plotting and analyzing Pandas DataFrames.
quak - Scalable, interactive data table, twitter.
data-formulator - Data visualization tool.

Environment and Jupyter

Jupyter Tricks
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.
handcalcs - More convenient way of writing mathematical equations in Jupyter.
notebooker - Productionize and schedule Jupyter Notebooks.
voila - Turn Jupyter notebooks into standalone web applications. Voila grid layout.

Jupyter Alternatives

positron - Data Science IDE.
Deepnote - Data Science platform with real-time collaboration, environment management.

Extraction + OCR

textract - Extract text from any document.
docling - Text extraction.
DeepSeek-OCR - OCR.
chandra - OCR.

Big Data

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.
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).

Command line tools, CSV

csvkit - Command line tool for CSV files.
csvsort - Sort large csv files.

Classical Statistics

Books

Lakens - Improving Your Statistical Inferences - Testing, Effect Sizes, Confidence Intervals, Sample Size, Equivalence Testing, Sequential Analysis, Github
Models Demystified - From Linear Regression to Deep Learning. Github.
The Math Behind Artificial Intelligence - Engineering-focused book covering linear algebra, calculus, probability & statistics, and optimization theory with Python examples.

Datasets

Rdatasets - Collection of more than 2000 datasets, stored as csv files (R package).
crimedatasets - Datasets focused on crimes, criminal activities (R package).
educationr - Datasets related to education (performance, learning methods, test scores, absenteeism) (R package).
MedDataSets - Datasets related to medicine, diseases, treatments, drugs, and public health (R package).
oncodatasets - Datasets focused on cancer research, survival rates, genetic studies, biomarkers, epidemiology (R package).
timeseriesdatasets_R - Time series datasets (R package).
usdatasets - US-exclusive datasets (crime, economics, education, finance, energy, healthcare) (R package).
economic datasets - Economic datasets.

p-values

The ASA Statement on p-Values: Context, Process, and Purpose
Greenland - Statistical tests, P-values, confidence intervals, and power: a guide to misinterpretations
Rubin - Inconsistent multiple testing corrections: The fallacy of using family-based error rates to make inferences about individual hypotheses
Gigerenzer - Mindless Statistics
Rubin - That's not a two-sided test! It's two one-sided tests! (TOST)
Lakens - How were we supposed to move beyond p < .05, and why didn’t we?
McShane et al. - Abandon Statistical Significance
Ho et al. - Moving beyond P values data analysis with estimation graphics
Lakens - The probability of p-values as a function of the statistical power of a test - p-value distribution is right-skewed and becomes even more skewed the higher the power of the test.

Correlation

Guess the Correlation - Correlation guessing game.
phik - Correlation between categorical, ordinal and interval variables.
hoeffd - Hoeffding's D Statistics, measure of dependence (R package).

Confidence Intervals

Morey - The fallacy of placing confidence in confidence intervals

Packages

statsmodels - Statistical tests.
linearmodels - Instrumental variable and panel data models.
nomograms - Visualization for linear models, explanation (Part of rms R package)
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
StatCheck - Extract statistics from articles and recompute p-values (R package).
tost - Two One-Sided Test (TOST) for equivalence.
DABEST-python - Mean difference plots.
Durga - Mean difference plots (R package).

Effect Size

MOTE Effect Size Calculator - Shiny App, R package
Estimating Effect Sizes From Pretest-Posttest-Control Group Designs - Scott B. Morris, Twitter

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

Power and Sample Size Calculations

pwrss - Statistical Power and Sample Size Calculation Tools (R package), Tutorial with t-test

Interim Analyses / Sequential Analysis / Stopping

Stop Early Stopping - Nice visualization Sequential Analysis - Wikipedia.
sequential - Exact Sequential Analysis for Poisson and Binomial Data (R package).
confseq - Uniform boundaries, confidence sequences, and always-valid p-values.

Visualizations

Friends don't let friends make certain types of data visualization
Great Overview over Visualizations
1 dataset, 100 visualizations
Dependent Propabilities
Null Hypothesis Significance Testing (NHST) and Sample Size Calculation
estimationstats - Online Tool for visualizing mean differences, effect sizes (Cohen's d) and others.
Sample Size / Duration Calculator
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

Tidy Tuesday

The Art of Data Visualization with ggplot2, The TidyTuesday Cookbook
Best Practices for Data Visualization
tidytuesday - Weekly challenge for visualization and lots of publicly available datasets for practice.
z3tt/TidyTuesday - Nice charts (R).
nrennie/tidytuesday - Nice charts (R).
poncest/tidytuesday - Nice charts (R).

Talks

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

Texts

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
Carlin et al. - On the uses and abuses of regression models: a call for reform of statistical practice and teaching
Chen, Roth - Logs with zeros? Some problems and solutions
Wigboldus et al. - Encourage Playing with Data and Discourage Questionable Reporting Practices
Simmons et al. - False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant
Zhang - An illusion of predictability in scientific results: Even experts confuse inferential uncertainty and outcome variability - Figure 1 shows difference between inferential uncertainty and outcome variability.

Evaluation

Collins et al. - Evaluation of clinical prediction models (part 1): from development to external validation - Twitter

Epidemiology

Lesko et al. - A Framework for Descriptive Epidemiology
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).
episensr - Quantitative Bias Analysis for Epidemiologic Data (=simulation of possible effects of different sources of bias) (R package).

Machine Learning Tutorials

Statistical Inference and Regression
Applied Machine Learning in Python
Convolutional Neural Networks for Visual Recognition - Stanford CS class.
Intuition for the Algorithms in Machine Learning - Lecture Series.

Exploration and Cleaning

Checklist.
pyjanitor - Clean messy column names.
skimpy - Create summary statistics of dataframes. Helpful clean_columns() function.
pandera - Data / Schema validation.
dataframely - Data / Schema validation.
pointblank - Data / Schema validation.
great_expectations - Data validation, documentation, and profiling for production pipelines.
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))
skrub - Bridge the gap between tabular data sources and machine-learning models.

Noisy Labels

cleanlab - Machine learning with noisy labels, finding mislabelled 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

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).
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.
pyhctsa - Time series feature engineering.
pypeln - Concurrent data pipelines.
feature-engine - Encoders, transformers, etc.

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

Selection

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
pymde - Minimum-distortion embedding with PyTorch, 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.

Packages

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: tsne-cuda, MulticoreTSNE, lvdmaaten
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).
generalized_contrastive_PCA - Generalized contrastive PCA.
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.
datamapplot - Tool for visualizing high dimensional data.

Visualization

All charts
physt - Better histograms, talk, notebook.
fast-histogram - Fast histograms.
matplotlib_venn - Venn diagrams.
penrose - Venn diagrams.
ridgeplot - Ridge plots.
mosaic plots - Categorical variable visualization, example.
yellowbrick - Visualizations for ML models (similar to scikit-plot).
bokeh - Interactive visualization library, Examples, Examples.
lets-plot - Plotting library.
plotnine - ggplot for Python.
altair - Declarative statistical visualization library.
hvplot - High-level plotting library built on top of holoviews.
dtreeviz - Decision tree visualization and model interpretation.
mpl-scatter-density - Scatter density plots. Alternative to 2d-histograms.
ComplexHeatmap - Complex heatmaps for multidimensional genomic data (R package).
morpheus - Broad Institute tool matrix visualization and analysis software. Source, Tutorial: 1, 2, Code.
jupyter-scatter - Interactive 2D scatter plot widget for Jupyter.
fastplotlib - Fast plotting library using pygfx.
datamapplot - Interactive 2D scatter plot.
SandDance - Interactive visualization tool from Microsoft.

Colors

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

Dashboards

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.

UI

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.
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.

Recommender Systems

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.

Decision Tree Models

Intro to Decision Trees and Random Forests, Another good visualization, 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.
supertree - Decision tree visualization.

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.
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.

Bio Image Analysis

Lee et al. - A beginner's guide to rigor and reproducibility in fluorescence imaging experiments
Awesome Cytodata

Tutorials

MIT 7.016 Introductory Biology, Fall 2018 - Videos 27, 28, and 29 talk about staining and imaging.
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.

Datasets

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.

Biostatistics / Robust statistics

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.

High-Content Screening Assay Design

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.

Microscopy + Assay

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.

Image Formats and Converters

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

Matrix Formats

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.

Image Viewers

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.
lightly-studio - Image annotation.

Napari Plugins

napari-sam - Segment Anything Plugin.
napari-chatgpt - ChatGPT Plugin.

Image Restoration and Denoising

aydin - Image denoising.
DivNoising - Unsupervised denoising method.
CSBDeep - Content-aware image restoration, Project page.
gibbs-diffusion - Image denoising.

Illumination correction

skimage - Illumination correction (CLAHE).
cidre - Illumination correction method for optical microscopy.
BaSiCPy - Background and Shading Correction of Optical Microscopy Images, BaSiC.

Bleedthrough correction / Spectral Unmixing

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.

Platforms and Pipelines

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.

Microscopy Pipelines

Labsyspharm Stack see below.
BiaPy - Bioimage analysis pipelines, paper.
SCIP - Image processing pipeline on top of Dask.
DeepCell Kiosk - Image analysis platform.
IMCWorkflow - Image analysis pipeline using steinbock, Twitter, Paper, workflow.

Labsyspharm

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.

Cell Segmentation

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.
instanseg - Cell segmentation.
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.
MedImageInsight - Embedding Model for General Domain Medical Imaging.
CHIEF - Clinical Histopathology Imaging Evaluation Foundation Model.

Cell Segmentation Datasets

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.

Evaluation

seg-eval - Cell segmentation performance evaluation without Ground Truth labels, Paper.

Feature Engineering Images

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.

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, 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.

Sequencing

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.

Drug discovery

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

Neural Networks

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.

Tutorials & Viewer

Google Tuning Playbook - A playbook for systematically maximizing the performance of deep learning models by Google.
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.

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.
pyvips - Faster image processing operations.

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 dataloader.

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.
litserve - Serve models.
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.

Computer Vision General

roboflow - Reusable computer vision tools.

Object detection / Instance Segmentation

Metrics reloaded: Recommendations for image analysis validation - Guide for choosing correct image analysis metrics, Code, Twitter Thread
Good Yolo Explanation
ultralytics - Easily accessible Yolo and SAM models.
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 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.

Transformers

The Annotated Transformer - Intro to transformers.
Transformers from Scratch - Intro.
Neural Networks: Zero to Hero - Video series on building neural networks.
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
TabPFN - Foundation Model 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).

GPU

cuML - RAPIDS, Run traditional tabular ML tasks on GPUs, Intro.
flashlib - A GPU library for classical machine-learning operators.

Regression

Ordinal Regression: paper
Understanding SVM Regression: slides, forum, paper
Generalized Additive Models - Tutorial in R.

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.

Classification

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

Steck et al. - Is Cosine-Similarity of Embeddings Really About Similarity?
scipy.spatial - All kinds of distance metrics.
vegdist - Distance metrics (R package).
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.

Clustering

Overview of clustering algorithms applied image data (= Deep Clustering).
Clustering with Deep Learning: Taxonomy and New Methods.
Hierarchical Cluster Analysis (R Tutorial) - Dendrogram, Tanglegram
Schubert - Stop using the elbow criterion for k-means and how to choose the number of clusters instead
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.
generalized-kmeans-clustering - Generalized k-means clustering.
evoc - Embedding Vector Oriented Clustering.

Clustering Evalutation

• 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

Multi-label classification

scikit-multilearn - Multi-label classification, talk.

Critical AI Texts

Sublime - The Return of Pseudosciences in Artificial Intelligence: Have Machine Learning and Deep Learning Forgotten Lessons from Statistics and History?

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) - 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.

Filtering in Python

scipy.signal

• Butterworth low-pass filter example
• Savitzky–Golay filter, W
  pandas.Series.rolling - Choose appropriate win_type.

Geometry

geomstats - Computations and statistics on manifolds with geometric structures.

Time Series

Time Series Anomaly Detection Review Paper
statsmodels - Time series analysis, seasonal decompose example, SARIMA, granger causality.
darts - Time Series library (LightGBM, Neural Networks).
kats - Time series prediction library by Facebook.
prophet - Time series prediction library by Facebook.
neural_prophet - Time series prediction built on PyTorch.
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.
timesfm - Pretrained Time Series Foundation Model from Google.
chronos - Pretrained language models for probabilistic time series forecasting by Amazon.

Time Series - Nixla

nixtla - Pretrained Time Series Foundation Model for forecasting and anomaly detection.
statsforecast - Forecasting with statistical and econometric models.
neuralforecast - Forecasting with neural networks.
mlforecast - Forecasting with ML models.
hierarchicalforecast - Hierarchical forecasting with statistical and econometric methods.

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.
rrcf - Robust Random Cut Forest algorithm for anomaly detection on streams.

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.

Ranking

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

Causal Inference

Texts

Chatton et al. - The Causal Cookbook: Recipes for Propensity Scores, G-Computation, and Doubly Robust Standardization
Statistical Rethinking - Video Lecture Series, Bayesian Statistics, Causal Models, R, python, numpyro1, numpyro2, tensorflow-probability.
Naimi et al. - An introduction to g methods
CS 594 Causal Inference and Learning
Marginal Effects Tutorial - Marginal Effects, g-computation and more.
Python Causality Handbook
The Effect: An Introduction to Research Design and Causality - Book
Structual Equation Modeling - Tutorial in R.

Tools

pecan - Online tool for building interactive perceived causal networks.
dagitty - Build causal DAG.
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.

Papers

Bours - Confounding
Bours - Effect Modification and Interaction

Probabilistic Modelling and Bayes

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.

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

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.

Model Uncertainty

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

Model Explanation, Interpretability, Feature Importance

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.
shapiq - Shapley interaction quantification.
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.

Automated Machine Learning

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.

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 - Modelling 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.
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.

Active Learning

Talk
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

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.

Containerization and Docker

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

Data Versioning, Databases, Pipelines and Model Serving

dvc - Version control for large files.
kedro - Build data pipelines.
feast - Feature store. Video.
pgvector - Vector similarity search for Postgres.
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.
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.
wandb - Experiment tracking, model versioning, and dataset visualization.
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

Resources

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

Guidelines

datasharing - Guide to data sharing.

Books

Blum - Foundations of Data Science
Chan - Introduction to Probability for Data Science
Colonescu - Principles of Econometrics with R
Rafael Irizarry - Introduction to Data Science (R Language)
Rafael Irizarry - Advanced Data Science (R Language)

Other Awesome Lists

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
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 MLOps
Awesome Neural Network Visualization
Awesome Online Machine Learning
Awesome Pipeline
Awesome Public APIs
Awesome Public Datasets
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 Visual Attentions
Awesome Visual Transformer

Lectures

NYU Deep Learning SP21 - YouTube Playlist.

Things I google a lot

Color Codes
Frequency codes for time series
Date parsing codes

Contributing

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.

License