Awesome Data Science
by academic · academic/awesome-datascience
An open-source Data Science repository to learn and apply toward real problems.
A full-fledged website about data science and analytics study material.
In-depth articles on AI, machine learning, and data science concepts with practical applications.
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Dabout helping professional programmers confidently apply machine learning algorithms to address complex problems.
Mlu is developed amazon to help people in ml space you can learn everything from basics here with live diagrams
NHow a Social Scientist Jumps into the World of Big Data
Educational content on software development, AI, and career growth in tech.
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VHandbook and recipes for data-driven solutions of real-world problems
Vis some of, all of, or much more than the above and this blog explores its impact on information technology, the business world, government agencies, and our lives.
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C↗A high-level guide to managing data science teams and projects.
Free GitHub version
A modern, open-access textbook on statistics with a heavy focus on data science applications.
MFocuses on the "art" of data analysis, how to ask the right questions and refine them.
A free FreeCodeCamp book teaching the math behind AI in plain English from an engineering point of view.
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2An expanding dataset of historical job postings from Luxembourg from 2020 to today. Free with 250k+ job postings hosted on AWS Data Exchange.
5Specific datasets for aircraft and Automatic Dependent Surveillance-Broadcast (ADS-B) sources.
AStructured dataset tracking 92 AI-attributed workforce reduction events affecting 453,748 workers across 12 countries and 11 sectors. JSON and CSV formats. CC-BY-4.0 licensed.
BAI-powered multi-market stock analysis with transparent BDE scoring across 73 stocks (US/HK/A-share). EU AI Act Art.50 compliant. MIT license.
Curated open dataset of 100+ Chinese teas with category, origin, caffeine level, flavor notes, oxidation, and brewing parameters. Available as JSON and CSV.
Free AI-powered tool that scores U.S. congressional STOCK Act trade disclosures by significance. Machine-scored signals from 537 lawmakers's public trade filings.
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COpen-data platform for Brazilian crime statistics. Neighborhood-level in Rio Grande do Sul (2.99M incidents across 79,024 neighborhoods, 2022–2025), municipality-level for MG and RJ, plus national PRF highway and DATASUS interpersonal-violence data. Free REST API, CSV/Parquet, daily updates, CC BY 4.0.
Open structured data on 1.9M+ species, including traits, classification, and media. Free API and bulk downloads for biodiversity and species-classification tasks.
Navigate the world of public data - Quickly search and analyze billions of public records published by governments, companies and organizations.
UN FAO statistics on food production, trade, land use, and emissions for 245+ countries. Free API and bulk download.
Financial datasets (stock market data, financial statements, sustainability data, and more).
FThe world's most comprehensive authoritative data source knowledge base. 210+ curated sources from governments, international organizations, and research institutions. MCP integration for AI agents. MIT licensed.
Global Biodiversity Information Facility: 2.4B+ species occurrence records. Free, open API for ecological modeling and ML research.
Institute for Health Metrics and Evaluation - a catalog of health and demographic datasets from around the world and including IHME results
Real-time news corpus with structured bias features across 15+ dimensions (3.2M+ articles, 5,000+ sources), live financial market data (stocks, ETFs, crypto) with AI-generated analysis, ML options pricing with probability metrics and full Greeks, historical options chain data for quantitative research; available via MCP server or REST API.
English dataset of Tokyo crime statistics across 5,078 neighborhoods × 7 years (36,222 records, 2018-2024), sourced from Tokyo Metropolitan Police open data. Includes interactive crime map, safety grading, and cost-of-living index. CC BY licensed.
LPython package for one-line access to 38 open research datasets from Latin America (health, neuroscience, mental health, economics). pip install latamdata-py.
provides a variety of data free of charge for uses that are freely available to the general public. Click on a data set below to learn more
Free platform archiving 6B+ animal movement records from GPS and satellite telemetry. Open REST API, useful for spatiotemporal modeling and trajectory ML.
Nasdaq Data Link A premier source for financial, economic and alternative datasets.
NFree corpora (over 6 billion tokens) mostly German (both historically and in contemporary German).
OPublic packaging product dataset generated from 1,000 exact-spec SKU records, with downloadable CSV and JSON files for ecommerce fulfillment and warehouse analysis.
Pan open source tool for running arbitrary queries against public data from the Stack Exchange network.
Structured reference dataset of 156 peptide and peptide-adjacent compounds, each with a regulatory status bucket, category, route, half-life, molecular weight, CAS number, reference count, and PubChem/DrugBank/Wikidata IDs. CSV and JSON, no login, CC BY 4.0.
A 30-metro composite ranking of how much of a $400K household income gets consumed by housing, taxes, childcare, healthcare, and transport. Open methodology, free, no email gate.
contains data sets good for machine learning
Filtered subset of NHTSA Fatality Analysis Reporting System covering 33,898 fatal crashes involving medium and heavy commercial trucks across all 50 US states, 2018-2024. Includes interactive Vision Zero Report Card comparing 19 cities, reproducible Python pipeline on GitHub, and HuggingFace mirror. Permanent DOI, CC BY 4.0.
VEvidence-graded dietary-supplement dataset covering dosing, bioavailability by form, drug-nutrient interactions, NHANES deficiency prevalence, FDA FAERS adverse-event signals, and cost-per-effective-dose, with every clinical claim citing a PubMed PMID. CC BY 4.0, DOI 10.57967/hf/9356.
ZFree ZIP-level environmental safety data for 42,000+ US ZIP codes: water quality, air quality, PFAS contamination, radon, lead, flood risk, and 11 more verticals. Public REST API, npm/PyPI packages, CC BY 4.0.
AProduction-ready AI agent development kit for Rust with model-agnostic design (Gemini, OpenAI, Anthropic), multiple agent types (LLM, Graph, Workflow), MCP support, and built-in telemetry.
AConvex Optimization (basics of convex analysis; least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems; optimality conditions, duality theory...)
DFree resources and learn what data science is and how it’s used in different industries.
HA hands-on course to train and deploy a serverless API that predicts crypto prices.
Introduction to machine learning covering basic theory, algorithms and applications
MSlides, scripts and materials for the Machine Learning in Finance course at NYU Tandon, 2022.
A free video series by Andrej Karpathy covering neural networks from scratch — backpropagation, makemore, GPT, and more.
Learn to prompt cutting-edge computer vision models with natural language, coordinate points, bounding boxes, segmentation masks, and even other images in this free course from DeepLearning.AI.
This course is designed to empower beginners with the essential skills to excel in today's data-driven world. The comprehensive curriculum will give you a solid foundation in statistics, programming, data visualization, and machine learning.
Free Course and Certification for building an end-to-end machine using W&B
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JA Java port of SciPy's signal processing module, offering filters, transformations, and other scientific computing utilities.
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AAI industry research and analysis with papers on AI pricing, enterprise adoption, and evaluation frameworks.
an international journal devoted to applications of statistical methods at large
Genetic Algorithm related Publications towards Data Science
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DProfessional courses in data analysis, statistics, and machine learning fundamentals.
course material on text-mining / corpus-linguistics in German funded by the federal state of North Rhine-Westphalia
course material: programming in python in German for digital humanities - funded by the federal state of North Rhine-Westphalia
is an intermediate/advanced level specialization focused on Recommender System on the Coursera platform.
. This is the mailing list for the Research Software Engineering in the Digital Humanities (DH-RSE) working group.
Chat with your database in natural language — no SQL needed. Get instant insights, build self-refreshing dashboards, and trigger automated workflows based on database changes.
AА fast and framework agnostic image augmentation library that implements a diverse set of augmentation techniques. Supports classification, segmentation, and detection out of the box. Was used to win a number of Deep Learning competitions at Kaggle, Topcoder and those that were a part of the CVPR workshops.
AAutomate code reviews and optimize application performance with ML-powered recommendations.
ASpot product defects using computer vision to automate quality inspection. Identify missing product components, vehicle and structure damage, and irregularities for comprehensive quality control.
AAWS Rekognition is a service that lets developers working with Amazon Web Services add image analysis to their applications. Catalog assets, automate workflows, and extract meaning from your media and applications.
AAutomatically extract printed text, handwriting, and data from any document.
Free End-to-End No-Code platform for text annotation and DL model training/tuning. Out-of-the-box support for Named Entity Recognition, Classification, Relation extraction and Assertion Status Spark NLP models. Unlimited support for users, teams, projects, documents.
AA platform for efficient, distributed, general-purpose data processing.
Apache Hama is an Apache Top-Level open source project, allowing you to do advanced analytics beyond MapReduce.
Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more
Arize AI community tier observability tool for monitoring machine learning models in production and root-causing issues such as data quality and performance drift.
MLOps in a notebook - uncover insights, surface problems, monitor, and fine tune your models.
Aureo.io is a low-code platform that focuses on building artificial intelligence. It provides users with the capability to create pipelines, automations and integrate them with artificial intelligence models – all with their basic data.
AAutoML to easily produce accurate predictions for image, text, tabular, time-series, and multi-modal data
AAn open-source Python package that extends the power of Pandas library to AWS connecting DataFrames and AWS data related services (Amazon Redshift, AWS Glue, Amazon Athena, Amazon EMR, etc).
CML powered analytics engine for outlier/anomaly detection and root cause analysis
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CAn open-source project that automatically maps relationship networks by parsing public data using LLMs and visualizes it as an interactive graph.
AI-powered academic citation generator. Searches 11+ scholarly databases (OpenAlex, PubMed, Semantic Scholar, CrossRef, SciELO) and formats references in 40+ citation styles. Available as web app, browser extension, Google Docs add-on, and public API.
CPython library for data-centric AI and automatically detecting various issues in ML datasets
CAn open source toolkit for using continuous integration in data science projects. Automatically train and test models in production-like environments with GitHub Actions & GitLab CI, and autogenerate visual reports on pull/merge requests.
CAn MLOps platform with experiment tracking, model production management, a model registry, and full data lineage to support your ML workflow from training straight through to production.
Software for corpus linguists and text/data mining enthusiasts. Build your own corpora in over 60 languages. Use over 50 tools/visualizations.
CAI-powered cryptocurrency trading bot with LSTM neural network (84.6% accuracy). Real-time pump detection, walk-forward validated models, multi-exchange support (Bybit, Binance, OKX, Gate.io). Open source.
A platform built on open source tools for data, model and pipeline management.
An open source Python library to painlessly transition your analytics code to distributed computing systems (Big Data)
A data science and engineering platform making Apache Spark more developer-friendly and cost-effective.
DTemplate repository for data science lifecycle project
easily explore, visualize, analyze, and transform data using familiar languages, such as Python and SQL, interactively.
An open source data visualization platform helping everyone to create simple, correct and embeddable charts. Also at github.com
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DAn agentic LLM for autonomous data science, which can autonomously complete a wide range of data science tasks without human intervention.
A new kind of data science notebook. Jupyter-compatible, with real-time collaboration and running in the cloud.
Track real-time GPU and LLM pricing across all cloud and inference providers.
DAn open-source data profiler specifically focused on discovery and validation of complex patterns, such as numerical association rules, differential dependencies, denial constraints, and more.
DSuperhuman exploratory data analysis. Finds the feature interactions and subgroup effects in tabular data that LLMs and manual exploration miss — with p-values, effect sizes, and literature citations. Free for public data.
DPersonal genome analysis toolkit with Python scripts analyzing raw DNA data across 17 categories (health risks, ancestry, pharmacogenomics, nutrition, psychology, and more) and generating a terminal-style single-page HTML visualization.
Run, scale, share, and deploy your models — without any infrastructure or setup.
DDAn open-source data science version control system. It helps track, organize and make data science projects reproducible. In its very basic scenario it helps version control and share large data and model files.
E🏕️ machine learning development environment for data science and AI/ML engineering teams
A search engine 🔎 tool to discover & find a curated list of popular & new libraries, top authors, trending project kits, discussions, tutorials & learning resources
FA feature store for the management, discovery, and access of machine learning features. Feast provides a consistent view of feature data for both model training and model serving.
FAn open source framework for automated feature engineering written in python
FSecure zero-knowledge encrypted file sharing (AES-256-GCM in-browser). No account required, MIT licensed, self-hostable, optional link expiry.
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FIndustrial-grade speech recognition toolkit supporting 50+ languages with built-in VAD, punctuation, speaker diarization, and emotion detection. OpenAI-compatible API server included.
FOpen-source platform to simulate, evaluate, trace, guardrail, route, and optimize LLM and AI agent apps in one feedback loop, so agents don't just get monitored, they self-improve. Self-hostable. Apache-2.0.
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GGrid studio is a web-based spreadsheet application with full integration of the Python programming language.
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HOpen-source data-intensive machine learning platform with a feature store. Ingest and manage features for both online (MySQL Cluster) and offline (Apache Hive) access, train and serve models at scale.
is a personal, portable Hadoop environment that comes with a dozen interactive Hadoop tutorials.
Popular open platform for sharing ML models, datasets, and collaborating on NLP and generative AI projects.
Ha service for exposing Apache Spark analytics jobs and machine learning models as realtime, batch or reactive web services.
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IInterpretML implements the Explainable Boosting Machine (EBM), a modern, fully interpretable machine learning model based on Generalized Additive Models (GAMs). This open-source package also provides visualization tools for EBMs, other glass-box models, and black-box explanations
high-level, high-performance dynamic programming language for technical computing
KAn unsupervised machine learning extension library for NetworkX with a Scikit-Learn like API.
KOpen-source Python framework for creating reproducible, maintainable data science code
The Kite Software Development Kit (Apache License, Version 2.0), or Kite for short, is a set of libraries, tools, examples, and documentation focused on making it easier to build systems on top of the Hadoop ecosystem.
Lis a workflow engine that significantly simplifies data analysis by combining in one analysis pipeline (i) feature engineering and machine learning (ii) model training and prediction (iii) table population and column evaluation.
LA Pytorch based framework that breaks down machine learning problems into smaller blocks that can be glued together seamlessly with an objective to build predictive models with one line of code.
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LEver been frustrated with cleaning up long, messy Jupyter notebooks? With LineaPy, an open source Python library, it takes as little as two lines of code to transform messy development code into production pipelines.
MMindsDB is an Explainable AutoML framework for developers. With MindsDB you can build, train and use state of the art ML models in as simple as one line of code.
MAll-in-one web-based IDE for machine learning and data science. The workspace is deployed as a Docker container and is preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch) and dev tools (e.g., Jupyter, VS Code)
An introductory yet powerful toolkit for natural language processing and classification
Community-friendly platform supporting data scientists in creating and sharing machine learning models. Neptune facilitates teamwork, infrastructure management, models comparison and reproducibility.
NA full-stack MLOps platform designed to help data scientists and machine learning practitioners around the world discover, create, and launch multi-cloud apps from their web browser.
This module covers some basic nlp principles and implementations. The main focus is performance. When we deal with sample or training data in nlp, we quickly run out of memory. Therefore every implementation in this module is written as stream to only hold that data in memory that is currently processed at any step.
NumPy is fundamental for scientific computing with Python. It supports large, multi-dimensional arrays and matrices and includes an assortment of high-level mathematical functions to operate on these arrays.
NFree open-source SPSS alternative — menu-driven desktop statistics (t-tests, ANOVA, regression, survival analysis, ROC) with SPSS .sav import/export
GNU Octave is a high-level interpreted language, primarily intended for numerical computations.(Free Matlab)
OEvaluate, test, and ship LLM applications across your dev and production lifecycles.
OCleansing, pre-processing, feature engineering, exploratory data analysis and easy ML with PySpark backend.
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PFast DataFrame library for Rust and Python, designed as a faster alternative to Pandas
PA Python Library for Probabalistic Programming (Bayesian Inference and Machine Learning)
Completely free enterprise-ready Python distribution for large-scale data processing, predictive analytics, and scientific computing
PPython Data Science Handbook: full text in Jupyter Notebooks
RIDE – powerful user interface for R. It’s free and open source, and works on Windows, Mac, and Linux.
RFast MATLAB-syntax runtime with automatic CPU/GPU execution and fused array kernels.
SciPy works with NumPy arrays and provides efficient routines for numerical integration and optimization.
SSA data-driven framework to quantify the value of classifiers in a machine learning ensemble.
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SA Python library to ease preprocessing and feature engineering for tabular machine learning
A Python-based inferential statistics, hypothesis testing and regression framework
SLightweight, Python library for fast and reproducible machine learning experimentation. Introduces very simple interface that enables clean machine learning pipeline design.
SCurated collection of the neural networks, transformers and models that make your machine learning work faster and more effective.
SAI-powered collaborative environment for research. Find relevant papers, create collections to manage bibliography, and summarize content — all in one place
TSynthetic tabular data generation using GANs, Diffusion Models, and LLMs with adversarial filtering and privacy metrics.
TTThe Data Science Lifecycle Process is a process for taking data science teams from Idea to Value repeatedly and sustainably. The process is documented in this repo
is an opinionated collection of R packages designed for data science. All packages share an underlying design philosophy, grammar, and data structures.
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TA terminal UI for experimenting with custom rule engines and selective LLM analysis on real-time data streams, without worrying about streaming infra or backpressure.
Easy-to-use text annotation tool for teams with most comprehensive auto-annotation features. Supports NER, relations and document classification as well as OCR annotation for invoice labeling
Vaex is a Python library that allows you to visualize large datasets and calculate statistics at high speeds.
An MLOps platform that handles machine orchestration, automatic reproducibility and deployment.
Build powerful data visualizations for the web without writing JavaScript
WWeka is a collection of machine learning algorithms for data mining tasks.
WOpen source “failure atlas” of 16 recurring issues in LLM and RAG pipelines, with observable symptoms and suggested fixes for data science teams.
Take numerical, textual, image, GIS or other data and give it the Wolfram treatment, carrying out a full spectrum of data science analysis and visualization and automatically generate rich interactive reports—all powered by the revolutionary knowledge-based Wolfram Language.
XA Python-powered shell that enables integration, management and orchestration of data science libraries mostly written in Python, allowing you to build pipelines, code and command-based workflows. It can also be used as a kernel for Jupyter Notebook.
ZCurated AI intelligence briefing from industry leaders covering models, funding, policy, and applications. 3x/week since 2017, 40K+ subscribers.
. Practical AI engineering and generative AI explained simply: RAG, agents, and LLM application patterns for builders.
. A free daily newsletter covering the most impactful developments in AI, ML, and tech. Archive.
1Job board focused on AI/ML engineering roles with 5,400+ listings and a free REST API.
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AA curated list of open-source tools for systematic reviews, meta-analysis, and evidence synthesis.
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M500+ ML/AI interview Q&A with runnable code — covers ML fundamentals, deep learning, NLP, PyTorch, scikit-learn pipelines, and system design
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MCP server that gives AI agents access to a database of scientific papers built from raw experimental data extracted from full-text studies. Returns 25+ structured fields per paper including methods, results, sample sizes, and quality scores. GitHub
COpen-source Python library and MCP server to benchmark document chunking strategies for RAG, score retrieval quality, and recommend configurations for a corpus.
IDaily-updated skill and CLI for deterministic retrieval across arXiv, PubMed/PMC, and supported US policy corpora.
x402 payment gateway with 23 Research & Reference endpoints for AI agents: Wikipedia, arXiv, PubMed, Wikidata, academic citation lookup, entity extraction, and more. Pay-per-call in USDC on Base & Solana — no API keys or subscriptions. Also serves 150+ endpoints across 39 categories including geospatial, AI inference, DeFi, and compute. GitHub
AI literature search, document translation, and deep-research workspace for researchers.
First Telegram Data Science channel. Covering all technical and popular staff about anything related to Data Science: AI, Big Data, Machine Learning, Statistics, general Math and the applications of former.
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TAOpen-source LLM and agent evaluation framework with 50+ metrics, LLM-as-Judge augmentation, and guardrail scanners (jailbreak, PII, prompt-injection). Useful for scoring RAG outputs, agent trajectories, and function-calling behavior in data-science workflows.
61 production-ready AI API tools for data science workflows: code analysis, web scraping, NLP, image generation, crypto data, and search. REST API and MCP protocol support. GitHub
CLocal AI agent for generating publication-ready scientific papers with real arXiv citations, IMRaD structure, and tribunal scoring. Runs 100% offline via Ollama with 4B-9B models. MIT licensed. HuggingFace
DAI crypto trading framework using LightGBM + XGBoost ensemble with 72 ML features. 70.9% walk-forward validated accuracy on out-of-sample data. Supports Bybit and Binance. MIT licensed, available on PyPI.
FMCP server providing 13 data tools for AI agents: real-time crypto prices, IP geolocation, DNS lookups, web scraping to markdown, code execution, and screenshots. One API key for 40+ services.
Search engine for AI agents that indexes 9,000+ AI tools and APIs, scoring each on agentic readiness (llms.txt, OpenAPI, MCP, ai-plugin.json). REST API and MCP server for programmatic tool discovery. GitHub
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DA developer handbook on designing and building effective AI agents.
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PInteractive calculator that visualizes the step-by-step manual math behind machine learning algorithms for exam prep.
TA straightforward method for training your LLM, from downloading data to generating text.
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TFree cross-platform search engine indexing 50,000+ tutorials from Udemy, Skillshare, Pluralsight, and other major learning platforms across 45+ categories.
Rapid-fire, live tryouts for data scientists seeking to monetize their models as trading strategies
Big Data, Data Science, Predictive Modeling, Business Analytics, Hadoop, Decision and Operations Research.
#datascientist @Ekimetrics. , #machinelearning #dataviz #DynamicCharts #Hadoop #R #Python #NLP #Bitcoin #dataenthousiast
Data Science Central is the industry's single resource for Big Data practitioners.
Data Science. Big Data. Data Hacks. Data Junkies. Data Startups. Open Data
Documenting my path from SQL Data Analyst pursuing an Engineering Master's Degree to Data Scientist
Mission is to help guide & advance careers in Data Science & Analytics
Tips and Tricks for Data Scientists around the world! #datascience #bigdata
Running with #BigData--enjoying a love/hate relationship with its hype. @iSchoolSU #DataScience Program Mgr.
KDnuggets President, Analytics/Big Data/Data Mining/Data Science expert, KDD & SIGKDD co-founder, was Chief Scientist at 2 startups, part-time philosopher.
Chief Scientist at RStudio, and an Adjunct Professor of Statistics at the University of Auckland, Stanford University, and Rice University.
Scientist at Facebook and Julia developer. Author of Machine Learning for Hackers and Bandit Algorithms for Website Optimization. Tweets reflect my views only.
The Economist's Data Editor and co-author of Big Data (http://www.big-data-book.com/).
PhD Student. Programming, Mobile, Web. Artificial Intelligence, Intelligent Robotics Machine Learning, Data Mining, Natural Language Processing, Data Science.
Opinions of full-stack Python guy, author, instructor, currently playing Data Scientist. Occasional fathering, husbanding, organic gardening.
Data @ Jawbone. Turned data into stories & products at LinkedIn. Text mining, applied machine learning, recommender systems. Ex-gamer, ex-machine coder; namer.