Tag · 31 repos
data-science
Repositories carrying the data-science tag.
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
The 30 Days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than 100 days. Follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
[NeurIPS 2026] DataFlex: A Unified Benchmark and Evaluation Platform for Data-Centric Training of Large Language Models
Fast and Accurate ML in 3 Lines of Code
🚀 FREE AI Resources - 🎓 Courses, 👷 Jobs, 📝 Blogs, 🔬 AI Research, and many more - for everyone!
🙌 Welcome open-source Python mini-project contributions!
Library to scrape and clean web pages to create massive datasets.
Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through R&D-Agent, which lets AI drive data-d
MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications.
A lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs in the web browser, on the desktop, on mobile, and inside Jupyter notebooks.
242 evaluated academic Claude/agent skills across 18 research domains — bioinformatics, cheminformatics, data science, databases, clinical, social science, Turkish academia & more. Every skill ships an executable eval. Citation verifier, research→write→review pipeline, 7 multi-agent workflows. Claud
Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
From "Math Isn't Hard": the two-volume 《Linear Algebra Isn't Hard》, covering 66 topics; feedback is welcome.
Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
A end-to-end MLOps pipeline for predicting telecom customer churn, featuring automated data preprocessing, ML model training, experiment tracking with MLflow, distributed training using PySpark, real-time inference via Kafka streaming, Airflow DAG orchestration, and Dockerized REST API deployment.
A complete, structured hub for learning Artificial Intelligence — covering AI, Machine Learning, Deep Learning, and Data Science with books, roadmaps, and curated resources from beginner to advanced.
The Open Source Feature Store for AI/ML
This repository is a curated collection of hands-on data science projects tailored for beginners. Whether you're just starting your journey in data science or looking to strengthen your skills, these projects provide a practical and interactive way to apply your knowledge.
10 Weeks, 20 Lessons, Data Science for All!
Type-safe, distributed orchestration of agents, ML pipelines, and real-time inference on your k8s — in pure Python with async/await, also other languages (rust, go and ts)
This project explores the potential for identifying stock market regimes , predicting stock market regimes and backtesting trading strategies based on those predictions.
A site that displays up to date COVID-19 stats, powered by fastpages.
Daniel15568/percentify — trending on GitHub.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Algorithmic Trading in Python with Machine Learning
Hopsworks - Data-Intensive AI platform with a Feature Store
The backtesting engine that gives you an unfair advantage. Run thousands of trading ideas before others finish one.
🐍 Python training in French, from beginner to advanced | 13 modules: OOP, asyncio, testing, FastAPI, SQLAlchemy, Data Science (NumPy/Pandas) | Python 3.12+ | MIT
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
Symbolic Learning in Python and Julia