Showing 81-100 of 332 projects
A comprehensive resource for learning deep reinforcement learning with Python and Jupyter Notebook.
A collection of Jupyter Notebook files for data analysis using Python, including a Chinese translation of the popular 'Python for Data Analysis' book.
Interactive computer science textbook covering algorithms, data structures, and complexity theory with Jupyter notebooks.
A Jupyter Notebook for teaching AI coding tools to microscopists
Create interactive web apps from Python notebooks with the mercury library.
A fast library for AutoML and hyperparameter tuning that can be used for various machine learning tasks.
Briefer is a powerful data visualization and reporting platform that enables vibe coders to create dashboards and notebooks with code.
Collection of 100+ Jupyter Notebook tutorials for fine-tuning AI models on various platforms.
Jupyter Notebook project to build large language models from scratch using Python, including GLM4, Llama3, and RWKV6.
Deepchecks is an open-source solution for thorough testing of ML models and data from research to production.
A Jupyter Notebook-based library for a whirlwind tour of Python for developers.
The Go kernel for Jupyter notebooks and nteract, enabling data science and numerical computing in Go.
A Jupyter Notebook project that helps developers label their own data and train custom AI models.
Interactive Jupyter notebooks for learning the fundamentals of computational fluid dynamics with Python.
An open-source threat hunting platform built on the ELK stack for security researchers and analysts.
A Python package for interactive geospatial analysis and visualization with Google Earth Engine.
A project that reimplements the 'Dive into Deep Learning' book's MXNet examples using TensorFlow 2.0 for vibe coders.
Jupyter notebooks for learning and experimenting with the popular scikit-learn machine learning library.
DeepAnalyze is an agentic LLM for autonomous data science, automating data analysis and report generation.
Polyaxon is an MLOps platform for managing and orchestrating the machine learning lifecycle.
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