Machine Learning
Showing 36 of 1845 projects
A Python framework for portfolio optimization using deep learning to allocate investment weights in a single forward pass.
A flexible, fast recommender engine for Python that integrates classic information filtering algorithms with scientific Python packages.
A GPU-accelerated deep learning library for Python using CUDA via PyCUDA, implementing neural networks with various training methods.
An open dataset and toolkit for training static PE malware machine learning models, featuring millions of labeled Windows executable samples.
An open dataset and toolkit for training static PE malware machine learning models, featuring extracted features from millions of Windows executable files.
A curated list of recent research papers and resources on Vision and Language Pre-trained Models (VL-PTMs).
A method to steer topic and attributes of GPT-2 language models without fine-tuning, enabling controlled text generation.
PySpark + Scikit-learn = Sparkit-learn
A curated list of Blockchain projects for Artificial Intelligence and Machine Learning.
An open-source study on neural question generation using transformers, providing simplified training and inference pipelines.
An autoML framework and toolkit for automating machine learning tasks on graph-structured data.
A lightweight header-only C++ library for running Keras (TensorFlow) models without linking against TensorFlow.
A collection of TensorFlow tutorials and examples covering image classification, GANs, text classification, and model deployment.
An open-source machine learning system for the end-to-end data science lifecycle from data preparation to model serving.
A curated collection of datasets, APIs, and tools for applying artificial intelligence and data mining to video games.
High-performance, end-to-end reinforcement learning implementations fully written in JAX for massive parallelization on GPUs.
A Kubernetes batch scheduler for high-performance workloads like AI/ML, BigData, and HPC.
A Python library implementing Factorization Machines with a scikit-learn compatible API for regression, classification, and ranking tasks.
An open-source Java framework for rapid development of machine learning and statistical applications with large dataset support.
A modular Python library for Reinforcement Learning with support for PyTorch, JAX, NVIDIA Warp, and multiple environment interfaces.
A modern, object-oriented machine learning framework for R, providing efficient building blocks for ML workflows.
A curated list of awesome resources, libraries, and tools for natural language processing (NLP) in Ruby.
A curated list of awesome resources, libraries, and tools for natural language processing (NLP) in Ruby.
A library of modular computer vision components built on Keras 3, supporting TensorFlow, JAX, and PyTorch backends.
A comparative Python framework for building, evaluating, and deploying multimodal recommender systems with auxiliary data.
Hardware-accelerated, batchable, and differentiable optimization algorithms implemented in JAX for machine learning research.
A curated collection of gradient boosting research papers with implementations from top machine learning conferences.
A TensorFlow-based GAN model that upscales images by 4x while generating photo-realistic details.
An embeddable vector database for Go with a Chroma-like interface, enabling RAG and semantic search without external dependencies.
A GPT-2 variant that generates plausible fake words, definitions, and usage examples from scratch.
A Python library for building Generalized Additive Models (GAMs) with a scikit-learn-like API, emphasizing interpretability and performance.
A Python package providing specialized statistical algorithms for graph and network analysis.
A PyTorch framework for training neural learning-to-rank models with flexible loss functions and scoring architectures.
An interactive visual interface for exploring and debugging black-box machine learning models without writing code.
A curated collection of machine learning resources, examples, and experiments for creative coding and education.
A modular framework for Torch providing abstractions for datasets, engines, meters, and logs to encourage code re-use.
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