Search Results for "algorithm" - Page 3
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Showing 291 open source projects for "algorithm"
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Vearch
A distributed system for embedding-based vector retrieval
...Through the module of the plugin, a complete default visual search system can be deployed just with one click. Otherwise, you can easily customize your own image, video, or text feature extraction algorithm plugin. This GIF provides a clear demonstration of the project vearch usage and its internal structure. The use of vearch is mainly divided into three steps. Firstly, create DB and Space, then import your data, and finally, you can search on your own dataset. -
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Manifest
🦞 Take control of your OpenClaw costs
Manifest is an open-source OpenClaw plugin designed to help users take control of their LLM costs through intelligent routing and real-time observability. Instead of sending every request to the same large model, Manifest intercepts each query and evaluates it using a 23-dimension scoring algorithm in under 2 milliseconds. It then routes the request to the most cost-effective and suitable model, potentially reducing costs by up to 90%. The platform includes a real-time dashboard that displays token usage, expenses, messages, and model activity in one place. Unlike cloud-based alternatives, Manifest runs entirely locally, ensuring that prompts, responses, and telemetry data never leave your machine. ... -
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NannyML
Detecting silent model failure. NannyML estimates performance
...When the actual outcome of your deployed prediction models is delayed, or even when post-deployment target labels are completely absent, you can use NannyML's CBPE-algorithm to estimate model performance. -
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Imagen - Pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network
Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior... -
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natural
General natural language facilities for node
"Natural" is a general natural language facility for nodejs. It offers a broad range of functionalities for natural language processing. Tokenizing, stemming, classification, phonetics, tf-idf, WordNet, string similarity, and some inflections are currently supported. It’s still in the early stages, so we’re very interested in bug reports, contributions and the like. Note that many algorithms from Rob Ellis’s node-nltools are being merged into this project and will be maintained from here... -
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MiniMax-M1
Open-weight, large-scale hybrid-attention reasoning model
MiniMax-M1 is presented as the world’s first open-weight, large-scale hybrid-attention reasoning model, designed to push the frontier of long-context, tool-using, and deeply “thinking” language models. It is built on the MiniMax-Text-01 foundation and keeps the same massive parameter budget, but reworks the attention and training setup for better reasoning and test-time compute scaling. Architecturally, it combines Mixture-of-Experts layers with lightning attention, enabling the model to... -
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Machine learning basics
Plain python implementations of basic machine learning algorithms
...The repository includes notebooks that demonstrate classic algorithms such as linear regression, logistic regression, k-nearest neighbors, decision trees, support vector machines, and clustering techniques. Each notebook typically combines explanatory text, Python code, and visualizations to illustrate how the algorithm operates and how it can be applied to datasets. -
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hbox
Sokoban solver written in Ada
This is a commandline-terminal sokoban solver written in Ada. It is "generic" in the sense that it contains no domain specific strategies. It also provides a demonstration of the incredible power of the Hungarian Algorithm. The proper command to extract the archive and maintain the directory structure is "7z x filename". -
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Machine Learning for Software Engineers
A complete daily plan for studying to become a machine learning engine
...The repository presents a top-down learning path that emphasizes hands-on experience rather than heavy theoretical prerequisites, making it particularly approachable for developers who already have programming experience but limited formal training in machine learning. The project organizes a multi-month study schedule that covers topics such as machine learning fundamentals, algorithm understanding, data preparation, and practical experimentation. It aggregates a wide range of resources including books, online courses, Kaggle competitions, podcasts, conferences, and community learning opportunities. The repository is structured to help learners gradually build the skills required for machine learning engineering positions while maintaining a focus on real-world application development. -
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Fractal Neuro Oscillator
A fractal neural network
...Gradient error values can then be calculated by subtracting out the differences in digest patterns. A Fractal Neuro Oscillator also can be trained to oscillate in a repeating manner via. a random training algorithm. The paper "Applications of Neuro Oscillators" which describes the network and how to use it is available in the files section. GUI based Python software that demonstrates the oscillator is also available. -
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Adaptive Intelligence
Adaptive Intelligence also known as "Artificial General Intelligence"
Adaptive Intelligence is the implementation of neural science, forensic psychology , behavioral science with machine-learning and artificial intelligence to provide advanced automated software platforms with the ability to adjust and thrive in dynamic environments by combining cognitive flexibility, emotional regulation, resilience, and practical problem-solving skills. -
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Bandicoot
fast C++ library for GPU linear algebra & scientific computing
* Fast GPU linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use * Provides high-level syntax and functionality deliberately similar to Matlab * Provides an API that is aiming to be compatible with Armadillo for easy transition between CPU and GPU linear algebra code * Useful for algorithm development directly in C++, or quick conversion of research code into production environments * Distributed under the permissive Apache 2.0 license, useful for both open-source and proprietary (closed-source) software * Can be used for machine learning, pattern recognition, computer vision, signal processing, bioinformatics, statistics, finance, etc * Downloads: http://coot.sourceforge.io/download.html * Documentation: http://coot.sourceforge.io/docs.html * Bug reports: http://coot.sourceforge.io/faq.html * Git repo: https://gitlab.com/conradsnicta/bandicoot-code -
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MegEngine
Easy-to-use deep learning framework with 3 key features
...Speed and precision problems won't bother you anymore due to the same core inside. In training, GPU memory usage could go down to one-third at the cost of only one additional line, which enables the DTR algorithm. Gain the lowest memory usage when inferencing a model by leveraging our unique pushdown memory planner. NOTE: MegEngine now supports Python installation on Linux-64bit/Windows-64bit/MacOS(CPU-Only)-10.14+/Android 7+(CPU-Only) platforms with Python from 3.5 to 3.8. On Windows 10 you can either install the Linux distribution through Windows Subsystem for Linux (WSL) or install the Windows distribution directly. ... -
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Evolutionary Computation Framework
C++ framework for application of any type of evolutionary computation.
ECF is a framework intended for application of any type of evolutionary computation (GA/GP, DE, Clonalg, ES, PSO, ABC, GAn, local search...). It offers simplicity for the end-user (parameterless usage, tutorial) and customization for experienced EC practicioners. -
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minbpe
Minimal, clean code for the Byte Pair Encoding (BPE) algorithm
minbpe is a minimal, clean implementation of byte-level Byte Pair Encoding (BPE), the tokenization approach widely used in modern language models. It operates on UTF-8 encoded bytes rather than Unicode characters, which makes it robust to arbitrary text inputs and avoids needing a language-specific character vocabulary. The repository is structured as a teaching-oriented implementation that shows how to train a tokenizer by learning merge rules, then apply those merges to encode text into... -
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TensorHouse
A collection of reference Jupyter notebooks and demo AI/ML application
TensorHouse is a scalable reinforcement learning (RL) platform that focuses on high-throughput experience generation and distributed training. It is designed to efficiently train agents across multiple environments and compute resources. TensorHouse enables flexible experiment management, making it suitable for large-scale RL experiments in both research and applied settings. -
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pattern_classification
A collection of tutorials and examples for solving machine learning
...The repository also covers algorithms such as Bayesian classification, logistic regression, neural networks, clustering methods, and ensemble models. In addition to algorithm tutorials, the project contains supplementary resources such as dataset collections, visualization examples, and links to recommended books and talks. These materials are designed to support both theoretical understanding and practical experimentation with machine learning tools. -
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TextGen
textgen, Text Generation models
...EDA, simple data augmentation technique: similar words, synonym replacement, random word insertion, deletion, replacement. This project refers to Google's UDA (non-core word replacement) algorithm and EDA algorithm, based on TF-IDF to replace some unimportant words in sentences with synonyms, random word insertion, deletion, replacement, etc. method, generating new text and implementing text augmentation This project realizes the back translation function based on Baidu translation API, first translate Chinese sentences into English, and then translate English into new Chinese. ... -
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Alink
Alink is the Machine Learning algorithm platform based on Flink
Alink is Alibaba’s scalable machine learning algorithm platform built on Apache Flink, designed for batch and stream data processing. It provides a wide variety of ready-to-use ML algorithms for tasks like classification, regression, clustering, recommendation, and more. Written in Java and Scala, Alink is suitable for enterprise-grade big data applications where performance and scalability are crucial. -
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The Algorithms - C #
Collection of various algorithms in mathematics, machine learning
...Within the C repository, contributors implement algorithms from many areas of computer science including sorting, searching, graph processing, mathematics, machine learning, and numerical methods. Each algorithm implementation is written to be readable and well documented so that students and developers can understand how the algorithm works internally. The repository is designed primarily as an educational resource that helps programmers study algorithm design and computational thinking. Contributors from around the world continually add new implementations and improvements, making the repository a collaborative learning project. -
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YoloV3 Implemented in TensorFlow 2.0
YoloV3 Implemented in Tensorflow 2.0
YoloV3 Implemented in TensorFlow 2.0 is built using TensorFlow 2.0. The project provides a modern deep learning implementation of the popular YOLOv3 algorithm, which is widely used for real-time object detection in images and video streams. YOLOv3 works by dividing an image into grid regions and predicting bounding boxes and class probabilities simultaneously, allowing objects to be detected quickly and efficiently. The repository includes training scripts, inference tools, and configuration files that make it possible to train custom object detection models on user-defined datasets. ... -
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AnyTrading
The most simple, flexible, and comprehensive OpenAI Gym trading
gym-anytrading is an OpenAI Gym-compatible environment designed for developing and testing reinforcement learning algorithms on trading strategies. It simulates trading environments for financial markets, including stocks and forex. -
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AB3DMOT
Official Python Implementation for "3D Multi-Object Tracking
...The system processes detection results from 3D object detectors that analyze LiDAR point clouds and uses them to track multiple objects across consecutive frames. Its tracking pipeline relies on a combination of classical algorithms, including a Kalman filter for state estimation and the Hungarian algorithm for data association between detected objects and existing tracks. This relatively simple design allows the tracker to achieve very high processing speeds while maintaining competitive tracking accuracy. The project also introduces new evaluation metrics specifically designed for assessing performance in 3D tracking benchmarks. ... -
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Lumi-HSP
This is an AI language model that can predict Heart failure or stroke
Using thsi AI model, you can predict the chances of heart stroke and heart failure. HIGLIGHTS : 1. Accuracy of this model is 95% 2. This model uses the powerful Machine Learning algorithm "GradientBoosting" for predicting the outcomes. 3. An easy to use model and accessible to everyone. -
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minimalRL-pytorch
Implementations of basic RL algorithms with minimal lines of codes
...Most experiments are designed to run quickly using the CartPole environment so that users can focus on understanding algorithm logic rather than computational infrastructure.
