stable-baselines3DLR-RM/stable-baselines3
PyTorch implementations of Stable Baselines (deep) reinforcement learning algorithms.
46 libraries, 10 updated this year
Go has a small but practical machine learning stack. gonum supplies matrices, statistics, optimization and plotting; golearn offers scikit-learn-style models; gorgonia builds computation graphs for neural networks; and GoCV binds OpenCV for computer vision. gota provides data frames.
46 libraries
PyTorch implementations of Stable Baselines (deep) reinforcement learning algorithms.
Self-contained Machine Learning and Natural Language Processing library in Go.
Dataframes for machine-learning and statistics (similar to pandas).
Word Embeddings: the full implementation of word2vec, GloVe in Go.
A pure Go implementation of the prediction part of GBRTs, including XGBoost and LightGBM.
GoNN is an implementation of Neural Network in Go Language, which includes BPNN, RBF, PCN.
Linear / Logistic regression, Neural Networks, Collaborative Filtering and Gaussian Multivariate Distribution.
A native Go clean room implementation of the Porter Stemming algorithm.
Fast and convenient feature processing for low latency machine learning in Go.
Plug-and-play, parallel Go framework for NeuroEvolution of Augmenting Topologies (NEAT).
Go binding for MXNet c_predict_api to do inference with a pre-trained model.
Benchmarks of machine learning inference for Go.
From-scratch Go port of tinygrad: a graph-rewrite ML compiler with reverse-mode autodiff and a WebGPU backend.
On-device streaming speech recognition runtime with C API for Linux (aarch64/x86_64). Based on NVIDIA NeMo FastConformer (80 ms cache-aware lookahead). Companion Silero VAD, wake-word, and 14-command KWS via same runtime.
Deep Neural Networks for Golang (powered by MXNet)
An open source Go transpiler for machine learning models.
An offline recommender system backend based on collaborative filtering written in Go.