Machine Learning
Showing 36 of 1845 projects
A visual debugger for TensorFlow with breakpoints and real-time data visualization during neural network training.
An R interface to TensorFlow, providing access to the complete TensorFlow API for numerical computation and machine learning.
Implementation of hyperparameter optimization methods for ML/DL models with sample code for regression and classification tasks.
A Java/Groovy/JavaFX data visualization tool for ETL, machine learning, and publishing web visualizations.
A discontinued Python neural network framework designed for fast, flexible experimentation with CPU and GPU backends.
Survival analysis built on top of scikit-learn
A curated collection of resources for deep learning applications in natural language processing.
Transpile trained scikit-learn estimators to C, Java, JavaScript, Go, PHP, and Ruby for embedded systems and performance-critical applications.
A real-time AI lakehouse platform with a Python-centric feature store and comprehensive MLOps capabilities.
Script to generate question/answer pairs from CNN and Daily Mail articles for machine reading comprehension research.
A minimalist neural network library optimized for sparse data and single-machine environments.
A PyTorch Lightning project template for structuring deep learning research code to ensure reproducibility and extensibility.
A lightweight and intuitive Go library for data manipulation, statistics, and machine learning using DataFrames.
A curated collection of Ruby libraries, tools, and resources for Natural Language Processing (NLP).
A deep learning framework for Julia inspired by Caffe, featuring modular architecture and multiple backends.
A Clojure library for neural networks, regression, and feature learning with GPU acceleration support.
A general-purpose machine learning library for Rust, focusing on speed and ease of use with minimal dependencies.
A web-based tool for automated hyperparameter tuning and stacked ensemble creation in Python.
A library for evaluating TensorFlow models on large datasets with distributed computation and slicing analysis.
Source code and tutorials for learning genetic algorithms and genetic programming in Python through hands-on example projects.
A Python framework for scalable time series forecasting using machine learning models, designed for production environments.
A Python toolbox for explainable AI, providing tools for data analysis, model evaluation, and bias mitigation in machine learning.
A curated list of resources for random forest and other tree-based machine learning methods.
A Python framework for processing spatio-temporal satellite imagery and extracting features for machine learning applications.
A curated collection of resources, papers, and frameworks for image-to-image translation research and applications.
A versatile Bayesian optimization package for hyperparameter optimization of machine learning algorithms.
A Java deep learning framework implementing neural networks with GPU acceleration via OpenCL and Aparapi.
A high-level builder API for TensorFlow that enables fluent, chainable neural network construction.
A Python library for parallel active learning of mathematical functions, intelligently sampling parameter spaces to minimize evaluations.
A deep learning JavaScript library built from scratch with PyTorch-like syntax and GPU acceleration via GPU.js.
A flexible Python framework for fast network flow data analysis, offering encrypted application identification, statistical feature extraction, and extensibility via plugins.
Deep Python bindings for Clojure enabling seamless interop, allowing Clojure to call Python libraries and vice versa.
A curated list of awesome information retrieval resources including books, courses, datasets, software, and conferences.
A curated list of awesome resources for information retrieval and web search, including books, courses, datasets, and software.
A computational framework for deep reinforcement learning experiments in traffic microsimulation and control.
An open-source library providing chest X-ray datasets, pre-trained models, and tools for medical imaging research and analysis.
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