Machine Learning
Showing 36 of 1845 projects
A Common Lisp library implementing evolutionary algorithms including Genetic Programming and Differential Evolution for optimization tasks.
A minimalistic Clojure library for statistical analysis, inference, and machine learning.
A JRuby gem providing Ruby interfaces for Weka's machine learning and data mining algorithms.
Saul is a declarative domain-specific language in Scala for designing flexible machine learning models with relational feature extraction.
An open-source solution for the Airbus Ship Detection Challenge, providing a benchmark and base for ship detection in satellite imagery.
A JavaScript library implementing logistic regression and C4.5 decision tree algorithms for machine learning in the browser and Node.js.
A Common Lisp implementation for Llama inference operations, enabling LLM experimentation and integration with symbolic AI systems.
Docker container with a CLI toolkit for generating datasets of packed executables and training ML models for packing detection.
Code for the Kaggle Dogs vs. Cats image classification competition using deep learning.
A differentiable ray tracing toolbox for radio propagation simulations, built on JAX for optimization and machine learning.
Detects humans in images and estimates their poses by identifying body parts and connecting them with pose lines.
A Julia package providing algorithms for regression analysis via regularized empirical risk minimization.
A Neovim file picker that learns your navigation patterns using a neural network to rank files by what you're most likely to open next.
A statistical machine learning tutorial explaining key generative models like diffusion, energy-based, VAE, and GAN models with intuitive analogies.
A deep learning algorithm that predicts type hints for Python code using neural networks.
A curated collection of machine-learned models for autonomous driving tasks like perception, prediction, and planning.
A lightweight deep learning library written in C++ with C, C#, and Python interfaces, supporting CPU and GPU computation.
A Blazor library that provides easy access to ML5.js machine learning models via JavaScript Interop.
Jupyter notebooks for hands-on Big Data Analytics exercise classes covering Spark ML, Map/Reduce algorithms, and deep learning.
An easy-to-use Python feature store for machine learning, optimized for timeseries data and built on Dask.
A comprehensive Random Forest implementation in Go with extensions for deep forests, continuous learning, feature selection, and anomaly detection.
A GitHub Action that retrieves model runs and metrics from Weights & Biases for integration into CI/CD workflows.
Random forest in Common Lisp
A Ruby client library for interacting with the Qdrant vector search database API.
A feedforward neural network implementation for JRuby that provides machine learning capabilities with Java backend performance.
Catkin-friendly C++ bindings for TensorFlow, enabling easy integration of TensorFlow C++ API into ROS projects.
A Haskell library implementing basic machine learning algorithms including Hopfield networks.
Kotlin implementations of TensorFlow Lite example Android apps for on-device machine learning.
Generates embedding vectors from audio files using a TensorFlow model trained on AudioSet, deployable as a Docker container.
A Ruby client library for interacting with the Weaviate vector search database API.
An interactive Swift PlaygroundBook that teaches neural network concepts through hands-on examples.
A Go package for reading word2vec vectors and performing similarity searches and analogies.
Rust bindings for LightGBM, enabling gradient boosting for machine learning tasks in Rust.
A curated list of academic papers, datasets, and metrics for 3D neurite segmentation in electron microscopy connectomics.
A high-level neural networks API for Delphi, written in Pascal with Python binding and support for TensorFlow, CNTK, or Theano backends.
A pre-trained BERT-based model for detecting positive or negative sentiment in short text fragments.
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