Machine Learning
Showing 36 of 1845 projects
A curated collection of Python tutorials and resources for data science, machine learning, and natural language processing.
A lightweight, single-binary Rust inference server providing 100% OpenAI-API compatible endpoints for local GGUF models.
A comprehensive toolset for converting, visualizing, and managing deep learning models across multiple frameworks like TensorFlow, PyTorch, and Caffe.
A fast, header-only C++ machine learning library with bindings for Python, R, Julia, and Go.
A TensorFlow implementation of a convolutional neural network for sentence classification based on Yoon Kim's paper.
A collection of TensorFlow tutorials covering basics to advanced neural network architectures with Python code and notebooks.
A privacy protection tool that adds imperceptible pixel-level changes to photos to prevent unauthorized facial recognition.
An open-source MLOps platform for building, orchestrating, and deploying production AI pipelines and agents.
A Python library implementing state-of-the-art deep reinforcement learning algorithms with seamless Keras integration.
An open-source machine learning framework for building classical, deep, or hybrid ML applications with a focus on performance and portability.
A TensorFlow implementation of neural style transfer that transforms images by applying artistic styles from one image to another.
Rust bindings for the C++ API of PyTorch, providing thin wrappers around libtorch.
Rust language bindings for TensorFlow, providing idiomatic access to machine learning capabilities.
A fast, flexible C++ standalone library for machine learning with high-performance defaults and total internal modifiability.
A fast, flexible C++ standalone library for machine learning with high-performance defaults and total internal modifiability.
An Emmy-winning perceptual video quality assessment algorithm that fuses multiple metrics to predict human visual quality.
A curated collection of papers, code, and resources for domain adaptation in machine learning.
A TensorFlow implementation of DeepMind's WaveNet neural network for generating raw audio waveforms.
A local-first, ML-powered desktop application for translating manga, built in Rust with automated text detection, OCR, inpainting, and LLM translation.
DeepMind's library for building graph networks in TensorFlow and Sonnet, enabling graph-structured data processing with neural networks.
Code repository for the 'Machine Learning with PyTorch and Scikit-Learn' book, providing practical examples and notebooks.
An end-to-end framework for building custom AI applications and agents directly integrated with databases.
A suite of GPU-accelerated machine learning algorithms with scikit-learn compatible APIs for 10-50x faster performance on large datasets.
An open-source library for building massively scalable machine learning pipelines on Apache Spark.
A high-performance Game Boy emulator written in Python, designed for AI training, game automation, and classic gameplay.
A compiler that extends SQL with AI capabilities to train, predict, and evaluate machine learning models directly from SQL statements.
A Python library providing extensions and utilities for data science and machine learning tasks.
A Python library for image augmentation in machine learning, offering a stochastic pipeline approach with fine-grained control over operations.
A Python library implementing hybrid recommendation algorithms with metadata support for both implicit and explicit feedback.
A hands-on beginner's guide to machine learning and image classification using Caffe and DIGITS with neural networks.
A curated list of awesome Generative Adversarial Network (GAN) applications and demonstrations across various domains.
A curated collection of links to conference publications, surveys, and software in graph-based deep learning.
A curated collection of resources for building, training, serving, and optimizing production-grade Large Language Model applications.
Run trained Keras models directly in the browser with GPU acceleration via WebGL.
A general-purpose tensor library for parallel computing across CPUs, GPUs, and hardware accelerators.
A Python library for lightning-fast univariate time series forecasting with optimized statistical and econometric models.
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