Search Results for "core vector regression"
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Showing 101 open source projects for "core vector regression"
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Visual Regression Tracker
Backend and Frontend application for tracking differences via image
Open source, self-hosted solution for visual testing and managing results of visual testing. Service receives images, performs pixel-by-pixel comparisons with its previously accepted baseline, and provides immediate results in order to catch unexpected changes. Use implemented libraries to integrate with existing automated suites by adding assertions based on image comparison. We provide native integration with automation libraries, core SDK and Rest API interfaces that allow the system to... -
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ZeusDB Vector Database
Blazing-fast vector DB with similarity search and metadata filtering
...Developers get multiple ingestion paths—batch, streaming, and upsert—making it easy to keep embeddings synchronized as content changes. Hybrid search is a core design goal, allowing you to mix vector, keyword, and filter queries in a single request for practical relevance. Observability and safety round out the system, with metrics, tracing, and guardrails to manage recalls, deletions, and privacy-sensitive data at scale. -
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Machine learning basics
Plain python implementations of basic machine learning algorithms
...Instead of relying on external machine learning libraries, the algorithms are implemented from scratch so that users can explore the mathematical logic and computational structure behind each technique. 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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Linfa
A Rust machine learning framework
linfa aims to provide a comprehensive toolkit to build Machine Learning applications with Rust. Kin in spirit to Python's scikit-learn, it focuses on common preprocessing tasks and classical ML algorithms for your everyday ML tasks. -
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dlib
Toolkit for making machine learning and data analysis applications
Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is... -
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MatlabMachine
Machine learning algorithms
Matlab-Machine is a comprehensive collection of machine learning algorithms implemented in MATLAB. It includes both basic and advanced techniques for classification, regression, clustering, and dimensionality reduction. Designed for educational and research purposes, the repository provides clear implementations that help users understand core ML concepts. -
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machine-learning-refined
Master the fundamentals of machine learning, deep learning
...Instead of presenting algorithms purely through mathematical derivations, the repository emphasizes geometric intuition, visualization, and step-by-step experimentation. It includes Jupyter notebooks and scripts that illustrate core machine learning topics such as regression, classification, optimization methods, and neural networks. These materials allow learners to see how algorithms behave during training and how different parameters affect model performance. -
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statsmodels
Statsmodels, statistical modeling and econometrics in Python
statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. An extensive list of result statistics are available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open source Modified BSD (3-clause) license. Generalized linear models with support for all... -
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QGIS
Cross platform (lin/win/mac) geographical information system (GIS)
...QGIS is a user-friendly open-source Geographic Information System (GIS) licensed under the GNU General Public License. QGIS is an official project of the Open Source Geospatial Foundation (OSGeo). It runs on Linux, Unix, Mac OSX, Windows and Android and supports numerous vector, raster, and database formats and functionalities. QGIS provides a continously growing number of capabilities provided by core functions and plugins. You can visualize, manage, edit, analyze data, and compose printable maps. We also collect case studies of how people all over the world use QGIS for their GIS work. You can view combinations of vector and raster data (in 2D or 3D) in different formats and projections without conversion to an internal or common format. -
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Oh My Fish
The Fish Shell Framework
Oh My Fish provides core infrastructure to allow you to install packages which extend or modify the look of your shell. It's fast, extensible and easy to use. Due to a regression bug in fish 2.6 with some terminal emulators, right prompts make the shell unusable. When called without arguments, update core and all installed packages. You can choose to update only the core, by running omf update omf. -
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XiangShan
Open-source high-performance RISC-V processor
XiangShan is an open-source, high-performance RISC-V processor project that implements out-of-order superscalar cores using Chisel for hardware construction. The design targets modern performance goals—deep pipelines, speculative execution, multi-issue decode/execute, and sophisticated branch prediction—while remaining synthesizable for ASIC flows and portable to FPGAs for research. A modular microarchitecture separates frontend, backend, and memory subsystems with coherent caches and... -
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Earth Engine API
Python and JavaScript bindings for calling the Earth Engine API
The Earth Engine API provides Python and JavaScript client libraries for Google Earth Engine, a planetary-scale geospatial analysis platform. With it, users compose lazy, server-side computations over massive catalogs of satellite imagery and vector datasets without handling raw files locally. The API exposes functional operators for map algebra, reducers, joins, and machine learning that scale transparently on Earth Engine’s backend. Developers authenticate once, work interactively in... -
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Vector Pascal is a language targeted at SIMD multi-core instruction-sets such as the AVX and SSE2 or x86-64-v3. It has a SIMD compiler which supports parallel vector operations, loop unrolling, common sub expression removal etc. It is implemented in Java.
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LangChain for .NET
C# implementation of LangChain
LangChain .NET is a C# implementation of the LangChain framework that enables developers to build LLM-powered applications using the .NET ecosystem. The project aims to replicate the core abstractions of LangChain, such as chains, agents, and vector stores, while adapting them to the conventions and strengths of C#. It emphasizes composability, allowing developers to build complex workflows by combining modular components that interact with language models and external data sources. The framework supports integration with multiple providers, including OpenAI and other compatible APIs, and includes tools for embeddings, document loading, and vector database interaction. ... -
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Neuron AI
The PHP Agentic Framework to build production-ready AI driven apps
Neuron AI is a PHP agentic framework for building production-ready AI applications that connect models, memory, vector databases, and tools into working agents. It is designed for developers who want to create systems such as RAG pipelines, multi-agent workflows, and business process automations without having to hand-build every integration from scratch. The framework provides an Agent class that can be extended to inherit core capabilities like memory, tools, function calling, and retrieval-augmented generation. ... -
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Hindsight
Hindsight: Agent Memory That Learns
Hindsight is an advanced, open-source memory system for AI agents designed to enable long-term learning, reasoning, and consistency across interactions by treating memory as a first-class component of intelligence rather than a simple retrieval layer. It addresses one of the core limitations of modern AI agents, which is their inability to retain and meaningfully use past experiences over time, by introducing a structured, biomimetic memory architecture inspired by how human memory works. Instead of relying solely on vector similarity or basic retrieval techniques, Hindsight organizes information into distinct categories such as facts, experiences, beliefs, and observations, allowing agents to differentiate between raw data and inferred knowledge. ... -
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DBreeze Database
C# .NET NOSQL ( key value store embedded ) ACID database
DBreeze Database is a professional, open-source, multi-paradigm (embedded Key-Value store, objects, NoSql, text search, multi-parameter search, embedding vector database, vector similarity search/clustering, etc.), multi-threaded, transactional and ACID-compliant data management system for .NET5> / .NET Framework 3.5> / Xamarin MONO Android iOS / .NET Core 1.0> / .NET Standard 1.6> / Universal Windows Platform / .NET Portable / UNITY / CoreRT. -
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mlr3
mlr3: Machine Learning in R - next generation
mlr3 is a modern, object-oriented R framework for machine learning. It provides core abstractions (tasks, learners, resamplings, measures, pipelines) implemented using R6 classes, enabling extensible, composable machine learning workflows. It focuses on clean design, scalability (large datasets), and integration into the wider R ecosystem via extension packages. Users can do classification, regression, survival analysis, clustering, hyperparameter tuning, benchmarking etc., often via companion packages. -
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Self-Hosted AI Starter Kit
Template that quickly sets up a local AI environment
The Self-Hosted AI Starter Kit is an open-source framework designed to help developers and teams quickly provision a local AI development environment that emphasizes control, privacy, and flexibility rather than dependence on external cloud APIs. At its core, the starter kit uses Docker Compose to orchestrate essential components like an AI workflow engine, vector database, local LLM server, and persistent storage, making it suitable for prototyping AI-driven applications without exposing sensitive data to third-party providers. It’s targeted at both technical and semi-technical users, allowing you to build custom AI workflows, chat experiences, or intelligent automation systems by integrating modular services that communicate via APIs; the setup is intended to be both repeatable and scalable for varied use cases. -
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PostgresML
The GPU-powered AI application database
...Combine and automate the entire workflow from embedding generation to indexing and querying for the simplest (and fastest) knowledge-based chatbot implementation. Leverage multiple types of natural language processing and machine learning models such as vector search and personalization with embeddings to improve search results. Leverage your data with time series forecasting to garner key business insights. Build statistical and predictive models with the full power of SQL and dozens of regression algorithms. Return results and detect fraud faster with ML at the database layer. PostgresML abstracts the data management overhead from the ML/AI lifecycle by enabling users to run ML/LLM models directly on a Postgres database. -
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two.js
A renderer agnostic two-dimensional drawing api for the web
...Two.js features a Scalable Vector Graphics Interpreter. This means developers and designers alike can create SVG elements in commercial applications like Adobe Illustrator and bring them into your two.js scene. -
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gensim
Topic Modelling for Humans
Gensim is a Python library for topic modeling, document indexing, and similarity retrieval with large corpora. The target audience is the natural language processing (NLP) and information retrieval (IR) community. -
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Thorium
High-performance, privacy-focused browser built as a fork of Chromium
Thorium is a high-performance, privacy-focused web browser built as a fork of Chromium. It is designed to deliver significantly faster browsing speeds through aggressive compiler optimizations such as SSE4.2 and AVX. These low-level enhancements allow Thorium to outperform standard Chrome and Chromium builds in responsiveness and efficiency. The browser removes much of Google’s built-in bloat to create a leaner browsing experience. Thorium also includes additional privacy features that... -
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nano-graphrag
A simple, easy-to-hack GraphRAG implementation
...GraphRAG expands traditional RAG pipelines by constructing knowledge graphs from documents and using relationships between entities to improve the quality and reasoning of AI responses. The nano-GraphRAG project focuses on reducing complexity by providing a compact and readable codebase that preserves the core functionality of graph-based retrieval systems while remaining easy to modify and extend. The system extracts entities and relationships from documents using language models and organizes them into graph structures that can be queried during generation. Developers can integrate different storage backends and embedding engines, including vector databases and graph databases such as Neo4j, allowing flexible experimentation with hybrid retrieval methods. -
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ML Sharp
Sharp Monocular View Synthesis in Less Than a Second
ML Sharp is a research code release that turns a single 2D photograph into a photorealistic 3D representation that can be rendered from nearby viewpoints. Instead of requiring multi-view input, it predicts the parameters of a 3D Gaussian scene representation directly from one image using a single forward pass through a neural network. The core idea is speed: the 3D representation is produced in under a second on a standard GPU, and then the resulting scene can be rendered in real time to...
