Search Results for "data processing" - Page 6
Sort By:
Showing 429 open source projects for "data processing"
View related business solutions-
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
1
mosdepth
fast BAM/CRAM depth calculation for WGS, exome, or targeted sequencing
mosdepth is a fast BAM/CRAM depth calculation tool for genomic data, allowing efficient computation of sequencing coverage. -
2
autoMate
AI tool for automating desktop tasks via natural language input
...Unlike conventional RPA tools that require predefined workflows, autoMate dynamically adapts to tasks by making autonomous decisions based on the current interface state. autoMate emphasizes local execution, meaning all processing happens on the user’s machine to maintain privacy and data security. -
3
LEANN
Local RAG engine for private multimodal knowledge search on devices
LEANN is an open source system designed to enable retrieval-augmented generation (RAG) and semantic search across personal data while running entirely on local devices. It focuses on dramatically reducing the storage overhead typically required for vector search and embedding indexes, enabling efficient large-scale knowledge retrieval on consumer hardware. LEANN introduces a storage-efficient approximate nearest neighbor index combined with on-the-fly embedding recomputation to avoid storing... -
4
TorchRL
A modular, primitive-first, python-first PyTorch library
TorchRL is an open-source Reinforcement Learning (RL) library for PyTorch. TorchRL provides PyTorch and python-first, low and high-level abstractions for RL that are intended to be efficient, modular, documented, and properly tested. The code is aimed at supporting research in RL. Most of it is written in Python in a highly modular way, such that researchers can easily swap components, transform them, or write new ones with little effort. -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
-
5
The Algorithms Python
All Algorithms implemented in Python
The Algorithms-Python project is a comprehensive collection of Python implementations for a wide range of algorithms and data structures. It serves primarily as an educational resource for learners and developers who want to understand how algorithms work under the hood. Each implementation is designed with clarity in mind, favoring readability and comprehension over performance optimization. The project covers various domains including mathematics, cryptography, machine learning, sorting,... -
6
blockfrost-python
Python 3 SDK for the Blockfrost.io API
API for Cardano decentralized blockchain. Accessing and processing information stored on the blockchain is not trivial. We provide abstraction between you and blockchain data, taking away the burden of complexity, so you can focus on what really matters - developing your applications. Our basic tier is and always will be free of charge. We nurture development and the Cardano ecosystem. However, if you want to support us, please consider upgrading. -
7
gain
Asyncio-based Python framework for building fast web crawling spiders
Gain is a Python web crawling framework designed to simplify the process of building efficient and scalable web scrapers. It is built on top of asynchronous technologies such as asyncio, aiohttp, and uvloop to support high-performance crawling with concurrent network requests. It provides a structured framework for creating spiders that can navigate websites, extract structured data, and process the collected results. Developers define crawlers using components such as spiders, parsers, and... -
8
Tweepy
Twitter for Python
An easy-to-use Python library for accessing the Twitter API. You can also use Git to clone the repository from GitHub to install the latest development version. The easiest way to install the latest version from PyPI is by using pip. Twitter requires all requests to use OAuth for authentication. The API class provides access to the entire twitter RESTful API methods. Each method can accept various parameters and return responses. When we invoke an API method most of the time returned back to... -
9
OpenAdapt
Open Source Generative Process Automation
OpenAdapt is the open source software adapter between Large Multimodal Models (LMMs) and traditional desktop and web Graphical User Interfaces (GUIs). OpenAdapt learns to automate your desktop and web workflows by observing your demonstrations. Spend less time on repetitive tasks and more on work that truly matters. Boost team productivity in HR operations. Automate candidate sourcing using LinkedIn Recruiter, LinkedIn Talent Solutions, GetProspect, Reply.io, outreach.io, Gmail/Outlook, and... -
99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
-
10
Memobase
Fast backend for long-term AI user memory via structured profiles
Memobase is an open source backend system that enables long-term user memory functionality for AI applications by capturing and structuring information about users across interactions. Its design centers on creating user profiles and recording event timelines, allowing AI systems to remember, understand, and evolve in their behaviour toward individual users over time. Instead of relying purely on traditional embedding-based retrieval or RAG systems, Memobase uses profile and timeline... -
11
Segmentation Models
Segmentation models with pretrained backbones. PyTorch
Segmentation models with pre trained backbones. High-level API (just two lines to create a neural network) 9 models architectures for binary and multi class segmentation (including legendary Unet) 124 available encoders (and 500+ encoders from timm) All encoders have pre-trained weights for faster and better convergence. Popular metrics and losses for training routines. All encoders have pretrained weights. Preparing your data the same way as during weights pre-training may give you better... -
12
Triton Inference Server
The Triton Inference Server provides an optimized cloud
...Triton enables teams to deploy any AI model from multiple deep learning and machine learning frameworks, including TensorRT, TensorFlow, PyTorch, ONNX, OpenVINO, Python, RAPIDS FIL, and more. Triton supports inference across cloud, data center, edge, and embedded devices on NVIDIA GPUs, x86 and ARM CPU, or AWS Inferentia. Triton delivers optimized performance for many query types, including real-time, batched, ensembles, and audio/video streaming. Provides Backend API that allows adding custom backends and pre/post-processing operations. Model pipelines using Ensembling or Business Logic Scripting (BLS). ... -
13
ComfyUI-3D-Pack
An extensive node suite that enables ComfyUI to process 3D inputs
ComfyUI-3D-Pack is an extension package for the ComfyUI visual AI workflow environment that enables users to generate and manipulate 3D assets using advanced machine learning techniques. ComfyUI itself is a node-based interface for designing and executing generative AI pipelines, and this extension expands its capabilities by introducing nodes specifically designed for working with three-dimensional data. The package allows the platform to process inputs such as meshes and UV textures and... -
14
diskover-community
Open source file indexing & storage analytics powered by Elasticsearch
Diskover Community Edition is an open source file system indexing and storage analytics platform designed to help organizations understand and manage large volumes of file data. It crawls file systems and indexes metadata using Elasticsearch, enabling fast search, analysis, and organization of files stored across different storage systems. It allows administrators and users to explore file structures, monitor storage usage, and gain insights into how data is distributed across... -
15
OpenClaw Medical Skills
The largest open-source medical AI skills library for OpenClaw
...This modular design allows developers and researchers to build AI systems that can access specialized medical reasoning processes, retrieve relevant biomedical information, and generate structured outputs suitable for analysis or downstream processing. -
16
go1pylib
go1pylib is a Python library designed to control the Go1 robot
go1pylib is a Python library designed to control the Go1 robot by Unitree Robotics. It provides an easy-to-use interface for robot movement, state management, collision avoidance, battery monitoring, and MQTT communication. Ideal for research and robotics development. -
17
TensorFlow
TensorFlow is an open source library for machine learning
Originally developed by Google for internal use, TensorFlow is an open source platform for machine learning. Available across all common operating systems (desktop, server and mobile), TensorFlow provides stable APIs for Python and C as well as APIs that are not guaranteed to be backwards compatible or are 3rd party for a variety of other languages. The platform can be easily deployed on multiple CPUs, GPUs and Google's proprietary chip, the tensor processing unit (TPU). TensorFlow... -
18
ProtoMotions
ProtoMotions is a GPU-accelerated simulation and learning framework
...It provides modular environments and learning components for animation, robotics, and reinforcement learning research. Large motion datasets such as AMASS and BONES can be divided across multiple GPUs for scalable policy training. A built-in PyRoki workflow retargets human motion data to different robot bodies with a single command. Policies can be tested across Isaac Gym, Isaac Lab, Newton, Genesis, MuJoCo, and high-fidelity Isaac Sim environments. Its deployment pipeline exports ONNX policies with observation processing included, simplifying transfers from simulation to real Unitree G1 hardware. The framework also supports procedural scene generation and motion authoring from Kimodo text-to-motion outputs. -
19
Semantic Router
Superfast AI decision making and processing of multi-modal data
Semantic Router is a superfast decision-making layer for your LLMs and agents. Rather than waiting for slow, unreliable LLM generations to make tool-use or safety decisions, we use the magic of semantic vector space — routing our requests using semantic meaning. Combining LLMs with deterministic rules means we can be confident that our AI systems behave as intended. Cramming agent tools into the limited context window is expensive, slow, and fundamentally limited. Semantic Router enables... -
20
UniMate
UniMate: One Unified Model to Animate Diverse Skeletons
...Inference can generate motion for unseen skeleton topologies without per-skeleton retraining or test-time optimization. The same model supports text-guided motion editing, in-betweening, and longer motion expansion. Training, inference, data processing, and preview checkpoints are provided for research use. -
21
hls4ml
Machine learning on FPGAs using HLS
...This approach allows machine learning algorithms to run directly on specialized hardware, making them suitable for applications that require extremely fast response times and minimal power consumption. The framework was originally developed for high-energy physics experiments where real-time decision systems must process large volumes of data with strict latency constraints. Over time, it has expanded to support a variety of scientific and industrial applications including signal processing, embedded systems, and biomedical monitoring. -
22
Hiring Agent
AI agent to evaluate and score resumes
...It reads a resume PDF and converts the content into Markdown-like text. It then uses a local or hosted language model to extract structured candidate information into sectioned JSON. The system can enrich that resume data with GitHub profile and repository signals when a profile is available. After the data is collected, it produces an explainable evaluation with category scores, supporting evidence, bonus points, and deductions. It can run locally with Ollama or use Google Gemini, which makes it flexible for teams that want either private local processing or hosted model access. -
23
Amazing-Python-Scripts
Curated collection of Amazing Python scripts
Amazing-Python-Scripts is a collaborative repository that collects a wide variety of Python scripts designed to demonstrate practical programming techniques and automation tasks. The project includes scripts ranging from beginner-level utilities to more advanced applications involving machine learning, data processing, and system automation. Its goal is to provide developers with useful coding examples that can solve everyday problems, automate repetitive tasks, or serve as learning exercises. The repository encourages community contributions, allowing developers to add their own scripts and improve existing ones through pull requests. ... -
24
stt
Voice Recognition to Text Tool
...It supports GPU acceleration if available, enabling faster processing on compatible hardware but still offers reliable performance on CPUs alone. -
25
LangExtract
A Python library for extracting structured information
...The system excels at handling long documents using optimized chunking, multi-pass extraction, and parallel processing to ensure both high recall and structured consistency.
