Data Science

Microsoft notebooks provides integrated Jupyter notebook experiences for Python and data science.

This collection links community detection research papers and their implementations.

A collection of machine learning and AI interview questions with code and cheat sheets for common data science libraries.

KDnuggets publishes news and articles about data science, machine learning, AI, and analytics.

Python developers can use Streamlit to build and share data applications.

ThrustCurve provides model and high-power hobby rocket motor data, including manufacturer specifications and certified performance.

Dataline lets users analyze and visualize data from files and databases through a chat interface.

NLR uses geographic information systems to create maps, analyses, models, applications, and visualizations for energy planning and production.

AWS Data Wrangler connects Pandas with AWS data services and databases, including Athena, Glue, Redshift, and S3.

19 Questions assigns attributes to objects using machine learning and Bayesian inference, according to its project description.

Apache Airflow lets users author, schedule, and monitor workflows programmatically.

ML-From-Scratch shares accessible NumPy implementations of machine learning models, from linear regression to deep learning.

oneDAL is a C++ and DPC++ library for accelerated machine learning routines on tabular data, governed by the UXL Foundation.

Analytics Vidhya’s DataHack platform offers data science challenges, hackathons, and learning resources.

OpenMetricLearning provides metric learning pipelines, models, and a model zoo.

A curated repository helps readers discover machine learning and AI courses published on YouTube.

The 30 Days of Python challenge provides step-by-step lessons for learning Python at an individually paced schedule.

PyTorch Lightning helps pretrain and fine-tune AI models across one or many GPUs with minimal code changes.

Explore a curated collection of big data frameworks, resources, and related projects.

Awesome Data Analysis collects more than 500 resources for data analysis and data science.

Data Science at Home is a technology podcast hosted by Francesco Gadaleta.

Python developers can use Dash to build data apps and dashboards without requiring JavaScript.

PipeRider provided code review tools for dbt data and has been superseded by Recce.

This repository collects software engineering, data science, AI, quant, product, and hardware internship listings for the 2027 summer cycle.