Showing 41-60 of 332 projects
An open-source data visualization and analytics component well-suited for large or streaming datasets.
A Jupyter Notebook-based AI image generation tool for developers building with AI tools and technologies.
An open-source Copilot for data scientists, enabling building high-performance portfolios, lab sites, and docs in Markdown and Jupyter.
A comprehensive repository for computer vision best practices, code samples, and documentation.
Custom Jupyter Notebook themes for syntax highlighting and UI customization.
A Jupyter Notebook book that teaches linear algebra and machine learning concepts using the power of matrices.
A Jupyter Notebook repository for learning and practicing prompt engineering for AI coding tools.
A Jupyter Notebook resource for understanding the fundamentals of deep learning.
Lab materials for an introductory course on deep learning from MIT, covering computer vision, music generation, and more.
A Jupyter Notebook project for zero-shot speech editing and text-to-speech using AI models.
Docker images containing Jupyter applications for data science and machine learning workflows.
A multi-user server for Jupyter notebooks, enabling collaborative data science and AI development.
100 days of algorithms in Jupyter Notebook for developers to learn and practice coding with AI tools
A curated collection of practical machine learning and data science notebooks and libraries across different industries.
An open-source Jupyter Notebook project for generating images with AI-powered Disco Diffusion models.
Evidently is an open-source ML and LLM observability framework to evaluate, test, and monitor AI-powered systems.
This is a repository with sample Python programs for learning Python, covering topics like NumPy, Pandas, and Jupyter Notebooks.
Jupytext is a library that allows Jupyter Notebooks to be saved and version-controlled as Markdown, Julia, Python or R scripts.
Python code for a book on probabilistic machine learning, with support for various ML frameworks.
NYU Deep Learning Spring 2020 project for building and experimenting with deep learning models using PyTorch.
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