hosford42

aiml_bot

An interpreter module for AIML (Artificial Intelligence Markup Language), implemented in pure Python

EngineeringIntelligence

An attempt to define intelligence concretely, so it can be implemented in software

TensorLayer

Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥

autokeras

AutoML library for deep learning

awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

basic_robot

Write mods without server restart while playing. Create custom machines that can build, dig, produce... Create your own games like minesweeper, sokoban,ctf, hide and seek...

best-of-ml-python

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

Cephalus

A Neural OS

CODE_TSAO_PNAS

code for "A topological solution to object segmentation and tracking"

collection

Collection of Hyperdimensional Computing Projects

d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.

datasets

🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools

dopamine

Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.

dragon

[NeurIPS 2022] DRAGON 🐲: Deep Bidirectional Language-Knowledge Graph Pretraining

example_continuous_control

G.pt

Official PyTorch Implementation of Learning to Learn with Generative Models of Neural Network Checkpoints

Kalman-and-Bayesian-Filters-in-Python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

lalrpop

LR(1) parser generator for Rust

lang-seg

Language-Driven Semantic Segmentation

MAE-pytorch

Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners

models-1

A collection of pre-trained, state-of-the-art models in the ONNX format

NLP-progress

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

paws

This dataset contains 108,463 human-labeled and 656k noisily labeled pairs that feature the importance of modeling structure, context, and word order information for the problem of paraphrase identification.

ppo-pytorch

Proximal policy optimization in PyTorch. Easy to read and understand.

TensorFlowGP

Genetic programming in TensorFlow

ThinkBayes2

Text and code for the forthcoming second edition of Think Bayes, by Allen Downey.

transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

vecsymr

Vector Symbolic Architecture (VSA) primitives for experimentation

VSA_basic_model

This project aims to develop a very basic Vector Symbolic Architecture model to use as a default model in my other VSA projects.

wikidetox

Experiments to help discussion on Wikipedia talk pages