Search Results for "deep learning ai"
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Showing 21 open source projects for "deep learning ai"
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ai-notebooks
Some ipython notebooks implementing AI algorithms
ai-notebooks is a collection of Jupyter notebooks that implements machine-learning and artificial-intelligence ideas in compact, inspectable experiments. The examples are written primarily in Python and use frameworks including TensorFlow, PyTorch, Keras, JAX, and tinygrad. Projects explore problems such as MNIST learning, GANs, VAEs, model compression, and knowledge distillation. -
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Rubix ML
A high-level machine learning and deep learning library for PHP
Rubix ML is a free open-source machine learning (ML) library that allows you to build programs that learn from your data using the PHP language. We provide tools for the entire machine learning life cycle from ETL to training, cross-validation, and production with over 40 supervised and unsupervised learning algorithms. In addition, we provide tutorials and other educational content to help you get started using ML in your projects. Our intuitive interface is quick to grasp while hiding alot... -
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FATE
An industrial grade federated learning framework
FATE (Federated AI Technology Enabler) is the world's first industrial grade federated learning open source framework to enable enterprises and institutions to collaborate on data while protecting data security and privacy. It implements secure computation protocols based on homomorphic encryption and multi-party computation (MPC). Supporting various federated learning scenarios, FATE now provides a host of federated learning algorithms, including logistic regression, tree-based algorithms, deep learning and transfer learning. ... -
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Python Outlier Detection
A Python toolbox for scalable outlier detection
PyOD is a comprehensive and scalable Python toolkit for detecting outlying objects in multivariate data. This exciting yet challenging field is commonly referred as outlier detection or anomaly detection. PyOD includes more than 30 detection algorithms, from classical LOF (SIGMOD 2000) to the latest COPOD (ICDM 2020) and SUOD (MLSys 2021). Since 2017, PyOD [AZNL19] has been successfully used in numerous academic researches and commercial products [AZHC+21, AZNHL19]. PyOD has multiple neural... -
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Exclusively Dark Image Dataset
ExDARK dataset is the largest collection of low-light images
...The dataset was created to address the lack of large-scale low-light datasets available for research in object detection, recognition, and enhancement. It has been widely used in studies of low-light image enhancement, deep learning approaches, and domain adaptation for vision models. Researchers can also explore its associated source code for low-light image enhancement tasks, making it an essential resource for advancing work in night-time and low-light visual recognition. -
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GraphEmbedding
Implementation and experiments of graph embedding algorithms
GraphEmbedding is an open-source Python project for implementing and experimenting with graph embedding algorithms. It follows a simple “graph in, embedding out” design. The library uses NetworkX graphs as input and produces vector representations for graph nodes. It includes implementations of DeepWalk, LINE, Node2Vec, SDNE, and Struc2Vec. Users can configure walks, embedding dimensions, training windows, epochs, and other model-specific parameters. Example scripts demonstrate how to train... -
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A rudimentary 3D computer game that utilises artificial neural networks to enable computer agents to anticipate a target's location and shoot (bullets) in the corresponding direction.
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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Reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI
Reinforcement-learning is a widely used educational repository that provides implementations, exercises, and solutions for a broad range of reinforcement learning algorithms, designed to complement foundational texts and courses in the field. The project collects popular approaches such as dynamic programming, Monte Carlo methods, temporal difference learning, Q-learning, SARSA, deep Q-networks, and policy gradient techniques, often demonstrated with Python and OpenAI Gym environments so users can experiment with agents learning in simulated tasks. ... -
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Real-ESRGAN
Real-ESRGAN aims at developing Practical Algorithms
Real-ESRGAN is a highly popular open-source project that provides practical algorithms for general image and video restoration using deep learning-based super-resolution techniques. It extends the original Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) approach by training on synthetic degradations to make results more robust on real-world images, effectively enhancing resolution, reducing noise/artifacts, and reconstructing fine detail in low-quality imagery. ... -
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DuranDuranbot
Teachable/trainable artificially intelligent music bot
A teachable/trainable artificially intelligent music bot fundamentally inspired by how the new wave band Duran Duran composes music. This program utilizes many algorithmic/AI techniques/processes, including machine learning; which allow you to teach/train it to compose music which you prefer... and the technique which is the foundation of the design of DuranDuranbot, which was directly inspired by how Duran Duran writes music........ Called, "bit by bit circular composition"....... and it's explanation can be found here - https://scsynth.org/t/bit-by-bit-circular-composition/1107 This program is written in the SuperCollider programming language - https://en.wikipedia.org/wiki/SuperCollider Contact - ken_brant@ymail.com -
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Detectron2
Next-generation platform for object detection and segmentation
Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark. It is powered by the PyTorch deep learning framework. Includes more features such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, etc. -
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MADDPG
Code for the MADDPG algorithm from a paper
MADDPG (Multi-Agent Deep Deterministic Policy Gradient) is the official code release from OpenAI’s paper Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. The repository implements a multi-agent reinforcement learning algorithm that extends DDPG to scenarios where multiple agents interact in shared environments. Each agent has its own policy, but training uses centralized critics conditioned on the observations and actions of all agents, enabling learning in cooperative, competitive, and mixed settings. ... -
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ESRGAN
Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution
ESRGAN stands for Enhanced Super-Resolution Generative Adversarial Network and is a foundational project in the field of deep learning-based image super-resolution. It builds on earlier GAN-based approaches by improving network architecture (e.g., using Residual-in-Residual Dense Blocks), adversarial loss functions, and perceptual loss components to generate higher-fidelity high-resolution images from low-resolution inputs with more realistic textures and details. -
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The Edge Machine Learning library
Machine learning algorithms for edge devices
Machine learning models for edge devices need to have a small footprint in terms of storage, prediction latency, and energy. One instance of where such models are desirable is resource-scarce devices and sensors in the Internet of Things (IoT) setting. Making real-time predictions locally on IoT devices without connecting to the cloud requires models that fit in a few kilobytes.These algorithms can train models for classical supervised learning problems with memory requirements that are... -
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The Mars Rover Simulator project is based on the evolutionary robotics paradigm where an artificial agent acquires its skills through the process of artificial evolution. This simulator can be useful to evolve neural network controllers for the rover
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Todbot is an AI addon to the gamestool virtual machine. The aim is to create an evolving neural network topology that should be capable of creating the optimal topology and network weighting to solve any problem given it.
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This chess program changes its strength to give the best match against you. Eventually it learns to beat you specifically through learning alogirthms. Features included transposition tables and a elementary 3-piece endgame tablebase.
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This is implementation of parallel genetic algorithm with "ring" insular topology. Algorithm provides a dynamic choice of genetic operators in the evolution of. The library supports the 26 genetic operators. This is cross-platform GA written in С++.
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The Free Connectionist Q-learning Java Framework is an library for developing learning systems. Keywords: qlearning, artificial intelligence, alife, neural nets, neural networks, machine learning, reinforcement learning unsupervised learning agents lejos
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Classic game solved with MinMax algorithm (full solution tree) and simple Heuristics. Specially for learning and teaching computer AI
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