Machine Learning
Showing 36 of 1845 projects
A learning-focused, high-performance tensor computation library built from scratch in Rust with automatic differentiation and CPU/CUDA backends.
Deploy and version machine learning models in Ruby applications using object storage like Amazon S3.
A TensorFlow implementation of Attend, Infer, Repeat (AIR), a generative model for fast scene understanding by reconstructing objects sequentially.
A comprehensive Java library for statistics, data mining, and machine learning with interactive notebook support.
A curated collection of resources for applying machine learning to biomedical and healthcare imaging applications.
A small machine learning library written in Clojure providing simple, concise implementations of ML algorithms.
A Docker-based speech recognition model that converts short English WAV audio files into text using Mozilla's DeepSpeech.
A neural network model that integrates neighbor information from heterogeneous networks to discover new drug-target interactions.
A modern, fast, and modular deep learning and machine learning framework for Python built on PyTorch.
Provides SigOpt wrappers for scikit-learn to optimize hyperparameters and facilitate model selection.
A Python library providing SigOpt hyperparameter optimization wrappers for scikit-learn and XGBoost models.
A machine learning framework for automated cell segmentation in bioimages using parametric spline curves.
A Go package for n-gram based text categorization and language detection with UTF-8 support.
A Go implementation of the NEAT (NeuroEvolution of Augmenting Topologies) algorithm for evolving neural network structures.
A multilayer perceptron neural network implementation in Go with backpropagation training.
A collection of neural network libraries for functional and mainstream languages, offering efficient lazy evaluation and cross-language compatibility.
A PyTorch-based Python library for energy-based machine learning models, including Restricted Boltzmann Machines and Deep Belief Networks.
A Go port of LIBSVM 3.14, providing support vector machine (SVM) algorithms for classification and regression.
A Deno module for matrix, ndarray, and tensor operations accelerated by WebGPU and WASM.
A fast and versatile implementation of support vector machines with integrated hyper-parameter selection and support for multiple learning scenarios.
A fungal image classification project using ResNet to identify mushroom species from citizen science and expert sources.
A TensorFlow/Keras LSTM model for hourly weather forecasting, offering univariate, multivariate, and multistep prediction modes.
A Ruby gem for scoring predictive models using PMML, supporting decision trees, naive Bayes, logistic regression, random forests, and gradient boosted trees.
OpenCV binding library for Common Lisp, compatible with OpenCV 2.4 and 3.x.
A simple implementation of the DAGGER imitation learning algorithm for autonomous steering control in the Torcs racing simulator.
A TensorFlow-based convolutional neural network for recognizing four-digit CAPTCHA images.
A Python package for generating multidimensional synthetic data using Copula and fPCA models to preserve statistical properties.
A machine learning approach for rapid, pathologist-level cell type annotation from spatial proteomics data like MIBI and CODEX.
A pattern recognition library for Go providing classification, clustering, and feature extraction algorithms.
A Clojure library providing machine learning algorithms with simple APIs for data preprocessing and modeling.
A collection of quantitative trading research experiments exploring uncommon strategies and techniques through Jupyter notebooks.
A JAX + Flax implementation of physics-inspired graph neural networks for solving combinatorial optimization problems like Max-Cut and Maximum Independent Set.
Go SDK for interacting with IBM Watson AI services, providing authentication, API clients, and utilities.
A deep similarity learning-based type inference tool for Python that provides ML-powered type auto-completion.
A JAX-based library for loopy belief propagation on discrete factor graphs, enabling efficient probabilistic inference.
Feature generation code for the Kaggle Acquire Valued Shoppers Challenge, focusing on customer behavior prediction.
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