Machine Learning
Showing 36 of 1845 projects
A public dataset of field images with segmentation masks and plant type annotations for computer vision in precision agriculture.
Bayesian text classifier for Go with flexible tokenizers and storage backends.
A Julia package for reproducible data setup, automating dataset downloads and management for scientific computing.
A scalable high-performance platform for R that enables large-scale machine learning, statistical analysis, and graph processing across clusters.
An open-source CAD framework for designing, simulating, and deploying deep neural networks on embedded platforms.
A deep learning model that classifies sounds in 10-second audio clips into 527 categories from the AudioSet ontology.
A Clojure/Java library for streaming, one-pass histograms that approximate data distributions for learning, visualization, and analysis.
A curated archive of research papers and resources on generative modeling, covering GANs, image synthesis, 3D generation, and applications.
A deprecated Node.js sample application demonstrating IBM Watson Natural Language Classifier service features.
Analyzes your Twitter personality using IBM Watson and matches you with similar celebrities based on their tweet content.
A full-featured Ruby implementation of Naive Bayes for probabilistic classification with customizable features.
Open-source implementation of the winning solution for the 2018 Data Science Bowl Kaggle competition using PyTorch and U-Net.
A Swift library for direct Neural Engine inference and training of transformers on Apple Silicon, bypassing CoreML for faster performance.
A large transformer foundation model for single-cell RNA sequencing data analysis, including gene network inference, denoising, and cell annotation.
A simple machine learning framework written in Swift, currently focusing on regression algorithms.
A pure, immutable module system for JAX that replaces PyTorch-style imperative coding with declarative parameter trees.
An open-source starter solution for the Kaggle Toxic Comment Classification Challenge, providing ready-to-use machine learning pipelines for detecting online harassment.
A PyTorch implementation combining Graph Convolutional Networks with OpenNMT-py for structured data to text generation.
A Clojure library implementing Hierarchical Temporal Memory (HTM) for temporal sequence learning and prediction.
An open platform for hosting and participating in data science challenges focused on open science and open data.
A deep bilinear attention network framework with adversarial domain adaptation for interpretable drug-target interaction prediction.
.NET Standard bindings for Apache MXNet, providing C# developers with NumPy-compatible APIs for machine learning model development, training, and deployment.
A Python toolkit for optimizing chemical reactions using machine learning strategies and benchmarks.
A type-safe, functional ONNX API and backend for deep learning and classical machine learning in Scala 3.
Interactive topic model visualization and interpretation library for Python, compatible with sklearn, Gensim, BERTopic, and Turftopic.
A .NET Standard library for accessing IBM Watson cognitive services like Assistant, Discovery, and Speech-to-Text.
A blockchain-based protocol for trustless evaluation and purchase of machine learning models on Ethereum.
A PyTorch Geometric extension library for signed and directed graph neural networks, embedding, and clustering methods.
A curated collection of databases, software, and papers for computational biology research.
A fast, flexible, and compact deep learning framework for Julia that runs on CPU and CUDA GPU.
A PyTorch implementation of the DeepDream algorithm for generating psychedelic, dream-like images from neural network activations.
A free, MIT-licensed object-oriented pattern recognition and machine learning toolbox for MATLAB.
Open-source software for deep learning-based analysis and visualization of whole slide images in digital pathology.
Spam filtering made easy for you
A Python toolbox using deep belief networks for topic modeling on document data, producing latent representations for content-based recommendation.
A JAX transform that implements LoRA (Low-Rank Adaptation) for efficient fine-tuning of large models with minimal memory overhead.
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