It implemented multi-perceptrons neural network (ニューラルネットワーク) based on Back Propagation Neural Networks (BPN) and designed unlimited-hidden-layers.
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Local-first CLI coding agent built with React and Ink.
A free video series by Andrej Karpathy covering neural networks from scratch — backpropagation, makemore, GPT, and more.
A low-level Linear Regression Engine utilizing the Ordinary Least Squares (OLS) method and QR decomposition.
An open-source coding agent built for low-cost and open-weight models.
Source code and experiments results for 2018 Data Science Bowl.
Source code and experiments results for Google AI Open Images - Object Detection Track.
Source code and experiments results for Home Credit Default Risk.
A small SDK for tools, handoffs, guardrails, tracing, and agent orchestration.
Examples and guides for using the OpenAI API.
Kilo - Open-source AI coding assistant for VS Code, JetBrains, and the CLI.
Vanna.ai - An open-source Python RAG framework for SQL generation and related functionality.
A library providing high-performance, easy-to-use data structures and data analysis tools.
Open-source platform to run coding agents as managed workers with tasks, approvals, budgets, and workspaces.
Build AI Assistants with memory, knowledge and tools.
A macOS app for browsing Claude Code sessions, exploring diffs, and re-running commands. Reads local transcripts, runs offline, open source.
Hidden Markov Models for Python, implemented in Cython for speed and efficiency.
Browse verified AI tools by use case, pricing, and category without the directory noise.
Peer-to-peer network of data owners and data scientists who can collectively train AI models using PySyft.
This fast-paced intro to programming with Python will have you writing code, solving problems, and making cool projects in no time.
Python bindings for ZPar, a statistical part-of-speech-tagger, constituency parser, and dependency parser for English.
R news and tutorials contributed by hundreds of R bloggers.
Decision-making tool powered by the latest GPT and in-context learning.
People are writing great tools and papers for improving outputs from GPT. Here are some cool ones we.