Topic: data-science

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.

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.

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

Summer 2027 software engineering, data science, AI, quant, product management, and hardware internship postings. Updated daily by Simplify and Pitt CSC.

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.

Easy Data Preparation with latest LLMs-based Operators and Pipelines.

Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

Data-Centric Pipelines and Data Versioning

Probabilistic time series modeling in Python

Visualizer for pandas data structures

WebApps in pure Python. No JavaScript, HTML and CSS needed

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

Summer 2027 software engineering, data science, AI, quant, product management, and hardware internship postings. Updated daily by Simplify and Pitt CSC.

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.

Easy Data Preparation with latest LLMs-based Operators and Pipelines.

Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.