Machine Learning
Showing 36 of 645 projects
A curated collection of hands-on data science project ideas and resources for learning machine learning and AI concepts.
A curated list of key papers and resources on implicit neural representations, a novel approach to parameterizing signals as continuous functions.
A Python library for explaining machine learning models using black-box, white-box, local, and global interpretation methods.
A curated list of network embedding techniques, including papers, implementations, and related resources for graph representation learning.
A JAX-native library implementing Monte Carlo tree search algorithms like AlphaZero and MuZero for reinforcement learning research.
A collection of beginner-friendly TensorFlow tutorials using Jupyter Notebook, covering deep learning fundamentals and practical applications.
A JavaScript application framework for machine learning and its engineering, designed for Web developers.
TensorFlow implementation of Deep Q-Networks (DQN) for human-level control in reinforcement learning environments.
A pure Python library for survival analysis, modeling time-to-event data with censoring.
An open-source deep learning API and server written in C++ that supports multiple backends like PyTorch, TensorRT, and TensorFlow for training and inference.
A real-time distributed analytical database built entirely on bitmaps for low-latency queries on fresh data.
A Python library for outlier, adversarial, and drift detection in machine learning models, supporting tabular, text, image, and time series data.
A Python tutorial and cookbook for implementing Bayesian modeling techniques using PyMC3.
A Go library that simplifies TensorFlow's Go bindings with method chaining, automatic scoping, and type conversion.
A general-purpose GPU compute framework built on Vulkan for cross-vendor graphics cards, enabling high-performance data processing and machine learning.
Identifies compilers, packers, obfuscators, and other characteristics in Android APK and DEX files.
A Python library for loading, shaping, embedding, and exploring large graphs with GPU-accelerated visualization and analytics.
A curated collection of research papers on decision, classification, and regression trees with implementations from top ML conferences.
A Jupyter Notebook kernel and interactive REPL for Go (golang) that enables interactive programming and data analysis.
A lightweight Python library for creating portable, expressive, and testable data transformation DAGs with built-in lineage and metadata.
A Python library for defining portable, modular, and testable data transformation DAGs with built-in lineage and metadata.
A ROS/ROS2 multi-robot simulator for autonomous vehicles, built on Unity HDRP for high-fidelity testing.
HyperLearn provides 2-2000x faster machine learning algorithms with 50% less memory usage, optimized for all hardware.
A curated list of community detection research papers with implementations.
An open-source framework for machine learning and other computations on decentralized data.
An intuitive Python library that adds single-line plotting functions for scikit-learn and other machine learning objects.
Rust bindings for the OpenCV computer vision library, enabling Rust developers to leverage OpenCV's capabilities.
A Python library for graph deep learning built on Keras and TensorFlow 2, providing flexible tools for graph neural networks.
A modular toolkit for machine learning, natural language processing, and text generation with TensorFlow and PyTorch versions.
A high-level neural network API for specifying and analyzing infinite-width neural networks as Gaussian Processes in Python.
A C++ library for fast approximate nearest neighbor searches in high-dimensional spaces with automatic algorithm selection.
A modular active learning framework for Python built on scikit-learn, enabling rapid creation of custom workflows.
A modular active learning framework for Python built on scikit-learn, enabling rapid creation of custom workflows.
A machine learning package implementing message passing neural networks for predicting molecular and reaction properties.
A large-scale dataset of object-centric video clips with 3D bounding box annotations and AR metadata for 3D object detection research.
A Python library for automatic differentiation that generates readable Python source code as its derivative output.
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