Python
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A curated repository of resources, tutorials, libraries, and tools for learning and applying data science to real-world problems.
A curated repository of resources, tutorials, libraries, and tools for learning and applying data science to real-world problems.
A curated repository of resources, tutorials, libraries, and tools for learning and applying data science to real-world problems.
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Composio powers 1000+ toolkits, tool search, context management, authentication, and a sandboxed workbench to help you build AI agents that turn intent into action.
A comprehensive collection of data science Python notebooks covering deep learning, machine learning, big data, visualization, and essential tools.
A top-down, hands-on daily study plan for software engineers transitioning into machine learning roles.
Open-source vector database and embedding store for building AI applications with semantic search.
An open-source data visualization and dashboard platform that connects to any data source, enabling teams to query, visualize, and share data insights.
An open-source data visualization and dashboard platform that connects to any data source, enabling teams to query, visualize, and share data insights.
Distributed Task Queue (development branch)
A Python library for building full-stack web applications with frontend and backend code entirely in Python.
A scalable, portable, and distributed gradient boosting library for efficient machine learning across multiple languages and platforms.
Data validation and settings management using Python type hints.
A Python library for data validation and settings management using Python type hints.
A library for automatically generating command line interfaces (CLIs) from any Python object.
An introduction to Bayesian inference and probabilistic programming using Python and PyMC, with a computational-first approach.
A deep learning library built on PyTorch that provides high-level components for rapid results and low-level components for research flexibility.
A deep learning library built on PyTorch that provides high-level components for rapid results and low-level components for research flexibility.
An open-source load testing tool that lets you write scalable performance tests in plain Python.
A curated list of insanely awesome libraries, packages, and resources for Quantitative Finance (Quants).
Open-source self-hosted web archiving tool that saves websites in multiple durable formats like HTML, PDF, and WARC.
Facebook AI Research's software system implementing state-of-the-art object detection algorithms like Mask R-CNN and RetinaNet.
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications in Python.
A fast, as-you-type, fuzzy-search code completion, comprehension, and refactoring engine for Vim with support for many languages.
Minimal inference code for running FLUX.1 open-weight models for image generation and editing.
Jupyter notebooks with example code and exercises from the first edition of Hands-on Machine Learning with Scikit-Learn and TensorFlow.
Open-source team chat with topic-based threading that combines the best of email and chat for productive remote work.
Minimal, clean, and well-documented implementations of data structures and algorithms in Python 3.
A cross-platform e-book manager for viewing, converting, editing, cataloging, and syncing e-books across devices.
The fastai book, published as Jupyter Notebooks, provides an introduction to deep learning, fastai, and PyTorch.
A cross-platform CLI tool that creates projects from customizable templates (cookiecutters) for any language or framework.
A cross-platform CLI tool that creates projects from customizable templates (cookiecutters) for any language or framework.
A cross-platform CLI utility that creates projects from project templates (cookiecutters) for any language or framework.
A production-grade Rust-native trading engine with deterministic event-driven architecture for multi-asset, multi-venue systems.
Companion materials and IPython notebooks for the 'Python for Data Analysis' book, covering pandas, NumPy, and data science workflows.
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