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
Apache Superset is a Data Visualization and Data Exploration Platform
scikit-learn: machine learning in Python
Deep Learning for humans
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Summer 2027 software engineering, data science, AI, quant, product management, and hardware internship postings. Updated daily by Simplify and Pitt CSC.
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Streamlit โ A faster way to build and share data apps.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Build and share delightful machine learning apps, all in Python. ๐ Star to support our work!
๐ซ Industrial-strength Natural Language Processing (NLP) in Python
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
๐ธ๏ธ Web apps in pure Python ๐
Data Apps & Dashboards for Python. No JavaScript Required.
Prefect is a workflow orchestration framework for building resilient data pipelines in Python.
matplotlib: plotting with Python
A reactive notebook for Python โ 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.
AKShare is an elegant and simple financial data interface library for Python, built for human beings! ๅผๆบ่ดข็ปๆฐๆฎๆฅๅฃๅบ
Best Practices on Recommendation Systems
Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
An orchestration platform for the development, production, and observation of data assets.
๐ฆ Data Versioning and ML Experiments
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-driven AI. ๐https://aka.ms/RD-Agent-Tech-Report
Statistical data visualization in Python
Rich MySQL Terminal Client with AutoCompletion, Syntax Highlighting, and Dataframes
Always know what to expect from your data.
Low-code framework for building custom LLMs, neural networks, and other AI models
Statsmodels: statistical modeling and econometrics in Python
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
PyMuPDF is a high performance Python library for data extraction, analysis, conversion & manipulation of PDF (and other) documents.
Fast and Accurate ML in 3 Lines of Code
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
A unified framework for machine learning with time series
A Python library for anomaly detection across tabular, time series, graph, text, image, and audio data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.
A python library for user-friendly forecasting and anomaly detection on time series.
The research engine that gives you an unfair advantage. Run thousands of trading ideas before others finish one.
A collection of machine learning examples and tutorials.
๐ง Build, run, and manage data pipelines for integrating and transforming data.
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
[SIGMOD'27] Easy Data Preparation with latest LLMs-based Operators and Pipelines.
โก TabPFN: Foundation Model for Tabular Data โก
Python Data. Leaflet.js Maps.
The Open Source Feature Store for AI/ML
Data processing for and with foundation models! ๐ ๐ ๐ฝ โก๏ธ โก๏ธ๐ธ ๐น ๐ท
๐ฉ Like builtins, but boltons. 250+ constructs, recipes, and snippets which extend (and rely on nothing but) the Python standard library. Nothing like Michael Bolton.
Aim ๐ซ โ An easy-to-use & supercharged open-source experiment tracker.
๐ Online machine learning in Python
A system for quickly generating training data with weak supervision
๐ :bar_chart: :bulb: Orange: Interactive data analysis
ZenML ๐: One AI Platform from Pipelines to Agents. https://zenml.io.
Probabilistic time series modeling in Python
A library of extension and helper modules for Python's data analysis and machine learning libraries.
Time series forecasting with PyTorch
Lightning โก๏ธ fast forecasting with statistical and econometric models.
Machine Learning and Computer Vision Engineer - Technical Interview Questions
DeepAnalyze is the first agentic LLM for autonomous data science. ๐ไฝ ็AIๆฐๆฎๅๆๅธ๏ผ่ชๅจๅๆๅคง้ๆฐๆฎ๏ผไธ้ฎ็ๆไธไธๅๆๆฅๅ๏ผ
โก๏ธSwanLab - an open-source, modern-design AI training tracking and visualization tool. Supports Cloud / Self-hosted use. Integrated with PyTorch / Transformers / verl / LLaMA Factory / ms-swift / Ultralytics / MMEngine / Keras etc.
STUMPY is a powerful and scalable Python library for modern time series analysis
pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
Symbolic Learning in Python and Julia