Showing 81-100 of 703 projects
An open-source data orchestration platform for developing, running, and observing data pipelines and workflows.
A powerful computer algebra system written in pure Python for scientific computing and math applications.
An open-source AutoML toolkit for automating the machine learning lifecycle, including feature engineering, neural architecture search, and hyperparameter tuning.
A comprehensive learning resource for data science and machine learning, covering a wide range of topics and tools.
A curated list of awesome big data frameworks, resources and other awesomeness.
Statistical data visualization in Python
A curated list of references for MLOps, the practice of managing and automating machine learning workflows.
A curated list of mind-expanding books covering various topics like computer science, philosophy, and more.
A Python library for fast, customizable, and interactive data profiling and exploratory data analysis.
A library of ready-to-use scientific skills for the Claude AI assistant, focused on bioinformatics, drug discovery, and scientific computing.
This repository provides Python training materials for business analysts and traders in the finance industry.
Comprehensive learning roadmap for AI & machine learning, with 200+ practical cases and projects for beginners to experts.
Trino is a distributed SQL query engine for big data, allowing fast, scalable, and cost-effective analytics.
A comprehensive code repository and resource for learning machine learning with Python.
A weekly curated list of top machine learning research papers, useful for vibe coders.
An open-source NLP research library built on PyTorch for advanced natural language processing tasks.
OpenRefine is a powerful data cleaning and transformation tool that helps developers work with messy data.
This is a fullstack tutorial covering backend technologies, architect path, and a developer community.
Low-code framework for building custom LLMs, neural networks, and other AI models
An R&D agent that automates high-value generic R&D processes to let AI drive data-driven AI.
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