Search Results for "development tools" - Page 2
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Showing 78 open source projects for "development tools"
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Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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MediaPipe Solutions
Cross-platform, customizable ML solutions
MediaPipe is an open-source framework developed by Google for building cross-platform machine learning pipelines that process audio, video, and other streaming data in real time. The system provides developers with tools and reusable components that allow them to combine multiple machine learning models with preprocessing and postprocessing logic into efficient perception pipelines. These pipelines can run on a wide variety of platforms including mobile devices, desktop systems, web... -
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DeepPavlov
A library for deep learning end-to-end dialog systems and chatbots
...Follow step-by-step instructions to install, configure and extend DeepPavlov framework for your use case. DeepPavlov is an open-source framework for chatbots and virtual assistants development. It has comprehensive and flexible tools that let developers and NLP researchers create production-ready conversational skills and complex multi-skill conversational assistants. Use BERT and other state-of-the-art deep learning models to solve classification, NER, Q&A and other NLP tasks. DeepPavlov Agent allows building industrial solutions with multi-skill integration via API services. -
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Seldon Core
An MLOps framework to package, deploy, monitor and manage models
The de facto standard open-source platform for rapidly deploying machine learning models on Kubernetes. Seldon Core, our open-source framework, makes it easier and faster to deploy your machine learning models and experiments at scale on Kubernetes. Seldon Core serves models built in any open-source or commercial model building framework. You can make use of powerful Kubernetes features like custom resource definitions to manage model graphs. And then connect your continuous integration and... -
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AWS Neuron
Powering Amazon custom machine learning chips
AWS Neuron is a software development kit (SDK) for running machine learning inference using AWS Inferentia chips. It consists of a compiler, run-time, and profiling tools that enable developers to run high-performance and low latency inference using AWS Inferentia-based Amazon EC2 Inf1 instances. Using Neuron developers can easily train their machine learning models on any popular framework such as TensorFlow, PyTorch, and MXNet, and run it optimally on Amazon EC2 Inf1 instances. ... -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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TNT
A lightweight library for PyTorch training tools and utilities
TNT is a lightweight training framework developed by Meta that simplifies the process of building and managing machine learning training loops using PyTorch. The project focuses on providing a flexible yet structured environment for implementing training pipelines without the complexity of large deep learning frameworks. It introduces modular abstractions that allow developers to organize training logic into reusable components such as trainers, evaluators, and callbacks. This design helps... -
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Karpathy
An agentic Machine Learning Engineer
karpathy is an experimental agentic machine learning engineer framework designed to automate many aspects of the ML development workflow. The project sets up a sandboxed environment where an AI agent can access datasets, run experiments, and generate machine learning artifacts through a web interface. Its startup script automatically prepares the environment by creating a sandbox directory, installing key ML libraries, and launching the agent interface. -
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C3
The goal of CLAIMED is to enable low-code/no-code rapid prototyping
C3 is an open-source framework designed to simplify the development and deployment of data science and machine learning workflows through reusable components and low-code development techniques. The framework focuses on enabling rapid prototyping while maintaining a path to production through automated CI/CD integration. CLAIMED provides a component-based architecture where data processing steps, models, and workflows can be packaged into reusable operators. -
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Adversarial Robustness Toolbox
Adversarial Robustness Toolbox (ART) - Python Library for ML security
Adversarial Robustness Toolbox (ART) is a Python library for Machine Learning Security. ART provides tools that enable developers and researchers to evaluate, defend, certify and verify Machine Learning models and applications against the adversarial threats of Evasion, Poisoning, Extraction, and Inference. ART supports all popular machine learning frameworks (TensorFlow, Keras, PyTorch, MXNet, sci-kit-learn, XGBoost, LightGBM, CatBoost, GPy, etc.), all data types (images, tables, audio,... -
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Machine Learning Zoomcamp
Learn ML engineering for free in 4 months
Machine Learning Zoomcamp is an open-source repository containing the materials for a comprehensive course that teaches machine learning engineering from fundamentals to deployment. The project is designed to guide learners through the complete lifecycle of developing machine learning systems, starting with data preparation and model training and ending with production deployment. Participants learn how to build regression and classification models using Python libraries such as NumPy,... -
Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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DeepDetect
Deep Learning API and Server in C++14 support for Caffe, PyTorch
The core idea is to remove the error sources and difficulties of Deep Learning applications by providing a safe haven of commoditized practices, all available as a single core. While the Open Source Deep Learning Server is the core element, with REST API, and multi-platform support that allows training & inference everywhere, the Deep Learning Platform allows higher level management for training neural network models and using them as if they were simple code snippets. Ready for applications... -
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Dlib is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
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TensorFlow Hub
A library for transfer learning by reusing parts of TensorFlow models
TensorFlow Hub is a repository that provides a library and platform for publishing, discovering, and reusing pre-trained machine learning models built with TensorFlow. The project enables developers to integrate high-quality models into their applications without needing to train them from scratch. Through TensorFlow Hub, researchers and practitioners can share reusable model components such as image classifiers, text embedding models, and object detection networks. These models can be... -
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YoloV3 Implemented in TensorFlow 2.0
YoloV3 Implemented in Tensorflow 2.0
...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. It also demonstrates how to integrate the model with TensorFlow’s high-level APIs such as Keras for easier experimentation and model development. The project supports both pretrained models and full training pipelines, enabling researchers and developers to adapt YOLOv3 for tasks such as surveillance, robotics, autonomous driving, and image analysis. -
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LLM Applications
A comprehensive guide to building RAG-based LLM applications
...It provides step-by-step guidance for constructing systems that ingest documents, split them into chunks, generate embeddings, index them in vector databases, and retrieve relevant context during inference. The repository also shows how these components can be scaled and deployed using distributed computing frameworks such as Ray. In addition to development workflows, the project includes notebooks, datasets, and evaluation tools that help developers experiment with different retrieval strategies and model configurations. -
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fastquant
Backtest and optimize your ML trading strategies with only 3 lines
fastquant is a Python library designed to simplify quantitative financial analysis and algorithmic trading strategy development. The project focuses on making backtesting accessible by providing a high-level interface that allows users to test investment strategies with only a few lines of code. It integrates historical market data sources and trading frameworks so that users can quickly build experiments without constructing complex data pipelines. The framework enables users to test common... -
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FlubuCore
A cross platform build and deployment automation system
"FlubuCore - Fluent Builder Core" is a cross-platform build and deployment automation system. You can define your build and deployment scripts in C# using an intuitive fluent interface. This gives you code completion, IntelliSense, debugging, FlubuCore custom analyzers, and native access to the whole .NET ecosystem inside of your scripts. FlubuCore offers a .net (core) console application that uses power of roslyn to compile and execute scripts. Intuitive and easy to learn. C#, fluent... -
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Promptify
se GPT or other prompt based models to get structured output
Promptify is an open-source Python library designed to simplify prompt engineering and the development of natural language processing pipelines using large language models. The project provides tools that help developers generate structured prompts for different NLP tasks and apply them across multiple generative AI systems. Instead of manually crafting prompts for each task, Promptify introduces a unified architecture that combines prompt templates, language model interfaces, and processing pipelines into a single framework. ... -
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CodeContests
Large dataset of coding contests designed for AI and ML model training
CodeContests, developed by Google DeepMind, is a large-scale competitive programming dataset designed for training and evaluating machine learning models on code generation and problem solving. This dataset played a central role in the development of AlphaCode, DeepMind’s model for solving programming problems at a human-competitive level, as published in Science. CodeContests aggregates problems and human-written solutions from multiple programming competition platforms, including AtCoder,... -
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UnionML
Build and deploy machine learning microservices
Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. Using industry-standard machine... -
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2020 Machine Learning Roadmap
A roadmap connecting many of the most important concepts
...The roadmap also highlights the major technologies and frameworks commonly used in machine learning development. In addition to describing technical tools, the project includes recommended learning resources that help users study the underlying mathematics and algorithms behind machine learning systems. The roadmap is often used as a high-level orientation tool for beginners who want to understand the broader landscape of machine learning. -
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DialoGPT
Large-scale pretraining for dialogue
DialoGPT is an open-source conversational language model developed by Microsoft Research for generating natural dialogue responses using large-scale transformer architectures. The system is built on the GPT-2 architecture and is designed specifically for multi-turn conversation tasks, enabling machines to produce coherent responses during interactive dialogue. The model was trained on a massive dataset of approximately 147 million conversational exchanges extracted from Reddit discussion... -
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Byzer-lang
A low-code open-source programming language for data pipeline
...Byzer is a SQL-like language, to simplify data pipeline, analytics, and AI, combined with built-in algorithms and extensions. We believe that everything is a table, a simple and powerful SQL-like language can significantly reduce human efforts of data development without switching different tools. -
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Guild AI
Experiment tracking, ML developer tools
...Guild AI simplifies hyperparameter tuning by applying state-of-the-art algorithms through straightforward commands, eliminating the need for complex trial setups. It also supports the automation of pipelines, accelerating model development, reducing errors, and providing measurable results. The toolkit is platform-agnostic, running on all major operating systems and integrating seamlessly with existing software engineering tools. Guild AI supports various remote storage types, including Amazon S3, Google Cloud Storage, Azure Blob Storage, and SSH servers. -
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Flashlight library
A C++ standalone library for machine learning
Flashlight is a fast, flexible machine learning library written entirely in C++ by Facebook AI Research and the creators of Torch, TensorFlow, Eigen, and Deep Speech. Native support in C++ and simple extensibility make Flashlight a powerful research framework that's hackable to its core and enables fast iteration on new experimental setups and algorithms with little unopinionated and without sacrificing performance. In a single repository, Flashlight provides apps for research across... -
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NSFW Data Scraper
Collection of scripts to aggregate image data
NSFW Data Scraper is an open-source project that provides scripts for automatically collecting large datasets of images intended for training NSFW image classification systems. The repository focuses on aggregating image data from various online sources so that developers can build datasets suitable for training content moderation models. These datasets typically contain images categorized into different classes associated with adult or explicit content, which can then be used to train...
