Search Results for "machine learning projects" - Page 43
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Showing 2393 open source projects for "machine learning projects"
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CollabAI
Enhance sales and satisfaction with Collab.ai's AI-driven platform.
Empowering businesses with AI-driven customer engagement solutions. Our innovative platform combines machine learning and natural language processing to automate interactions, boost sales, and enhance customer satisfaction. Experience the future of customer engagement with Collab.ai – where every interaction drives growth and success. -
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ChemCrow
Chemcrow
ChemCrow is an AI-powered framework designed to assist in chemical research and discovery. It integrates AI models with chemical knowledge bases to provide intelligent recommendations for synthesis planning, reaction prediction, and material discovery. This tool helps automate and accelerate research in computational chemistry and drug development. -
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Featureform
Turn your existing data infrastructure into a feature store
Featureform allows data scientists to define, manage, and serve machine learning features across your organization. The days of untitled_128.ipynb are over. Transformations, features, and training sets can be pushed from notebooks to a centralized feature repository with metadata like name, variant, lineage, and owner. Featureform's Virtual Feature Store architecture orchestrates your data infrastructure to build and maintain your training sets and production features. ... -
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Autodistill
Images to inference with no labeling
Autodistill uses big, slower foundation models to train small, faster supervised models. Using autodistill, you can go from unlabeled images to inference on a custom model running at the edge with no human intervention in between. You can use Autodistill on your own hardware, or use the Roboflow hosted version of Autodistill to label images in the cloud. -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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TorchQuantum
A PyTorch-based framework for Quantum Classical Simulation
A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers. Researchers on quantum algorithm design, parameterized quantum circuit training, quantum optimal control, quantum machine learning, and quantum neural networks. Dynamic computation graph, automatic gradient computation, fast GPU support, batch model terrorized processing. -
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AIConfig
AIConfig is a config-based framework to build generative AI apps
...The framework allows prompts, model configurations, and parameters to be stored as structured configuration files that can be version controlled and managed independently from the rest of the software system. This approach improves collaboration between developers, prompt engineers, and machine learning practitioners by turning prompt logic into a reusable and editable artifact. AIConfig supports multiple model providers and modalities, enabling developers to experiment with different models without rewriting application logic. The configuration format is JSON-serializable and integrates with tools such as Python and Node SDKs, allowing the same configuration file to be used across multiple environments. -
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MeloTTS
High-quality multi-lingual text-to-speech library by MyShell.ai
MeloTTS is an open-source text-to-speech (TTS) system that generates natural-sounding speech from text input. It utilizes advanced machine-learning models to produce high-quality audio outputs. -
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VCClient
Software that uses AI to perform real-time voice conversion
VCClient is a real-time voice conversion system that uses machine learning models to transform a speaker’s voice into another voice with minimal latency. It is designed for live applications such as streaming, gaming, and virtual communication, where immediate feedback is essential. The system supports multiple voice conversion models, including RVC and other neural network-based approaches, allowing users to switch between different voices or customize their output. -
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MATLAB and Simulink for Students
An awesome list of helpful resources for students learning MATLAB
Are you a new MATLAB user seeking helpful tips and tricks? Are you a member of a student society in search of engaging workshops? Or perhaps you're looking for opportunities to test your MATLAB skills through student competitions or challenges? Look no further! Our awesome list repository below is a resource that caters to all these needs. Whether you're starting from scratch or aiming to enhance your existing knowledge, you'll find a wealth of information to help you learn MATLAB and make... -
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Qvid
Stream low latency video from your desktop or webcam over TCP/IP
...It allows you to capture screenshots of your desktop, webcam, and selected windows programs. The captured images are compressed and sent as a continuous stream over a TCP connection to a single machine. Developed alongside https://sourceforge.net/projects/netjoy/ to allow for off-site, single and multiplayer, game play over an internet connection. -
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Greenplum Database
Massive parallel data platform for analytics, machine learning and AI
Rapidly create and deploy models for complex applications in cybersecurity, predictive maintenance, risk management, fraud detection, and many other areas. With its unique cost-based query optimizer designed for large-scale data workloads, Greenplum scales interactive and batch-mode analytics to large datasets in the petabytes without degrading query performance and throughput. Based on PostgreSQL, Greenplum provides you with more control over the software you deploy, reducing vendor... -
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Azure Zero to Hero Course
Repository to learn Azure from Zero
Azure Zero to Hero Course is a comprehensive, day-by-day course repository designed to teach Azure fundamentals and practical skills from the ground up, targeted especially at aspiring DevOps engineers. The README is structured as a multi-day curriculum: early days cover cloud concepts, terminology, and Azure basics such as regions, availability zones, resource groups, and VM creation. Subsequent days dive into networking (VNets, subnets, NSGs, load balancers, firewalls), storage services,... -
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ML YouTube Courses
Discover the latest machine learning / AI courses on YouTube
ML YouTube Courses is a curated index of high-quality machine learning and AI courses available on YouTube, designed to make open education easier to discover and navigate. The repository organizes lectures from top universities and educators into a structured list so learners can quickly find reputable material. It covers a wide range of topics including deep learning, NLP, probabilistic modeling, reinforcement learning, and computer vision. -
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dinrhiw2-180824-sync
Dinrhiw2 is open source machine learning library.
Dinrhiw2 is open source machine learning library. -
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OnnxStream
Lightweight inference library for ONNX files, written in C++
The challenge is to run Stable Diffusion 1.5, which includes a large transformer model with almost 1 billion parameters, on a Raspberry Pi Zero 2, which is a microcomputer with 512MB of RAM, without adding more swap space and without offloading intermediate results on disk. The recommended minimum RAM/VRAM for Stable Diffusion 1.5 is typically 8GB. Generally, major machine learning frameworks and libraries are focused on minimizing inference latency and/or maximizing throughput, all of which at the cost of RAM usage. So I decided to write a super small and hackable inference library specifically focused on minimizing memory consumption: OnnxStream. OnnxStream is based on the idea of decoupling the inference engine from the component responsible for providing the model weights, which is a class derived from WeightsProvider. ... -
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Neural Networks: Zero to Hero
A course on neural networks that starts all the way at the basics
Neural Networks: Zero to Hero is Andrej Karpathy’s educational course repository for learning neural networks from the ground up. It accompanies a series of video lectures where learners code and train neural networks step by step. The project starts from basic concepts and gradually builds toward more capable character-level language models. Its notebooks are written to make the mechanics visible, so learners can understand gradients, backpropagation, embeddings, multilayer perceptrons,... -
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Sonnet
TensorFlow-based neural network library
Sonnet is a neural network library built on top of TensorFlow designed to provide simple, composable abstractions for machine learning research. Sonnet can be used to build neural networks for various purposes, including different types of learning. Sonnet’s programming model revolves around a single concept: modules. These modules can hold references to parameters, other modules and methods that apply some function on the user input. There are a number of predefined modules that already ship with Sonnet, making it quite powerful and yet simple at the same time. ... -
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OpenAI Quickstart Python
Python example app from the OpenAI API quickstart tutorial
openai-quickstart-python is an official OpenAI repository containing multiple Python quickstart applications that demonstrate how to use different OpenAI API endpoints, including Chat and Assistants. It provides practical, beginner-friendly examples to help developers quickly learn how to send requests, handle responses, and build basic applications using the OpenAI Python SDK. The examples folder includes small, self-contained projects showcasing common use cases like chat completions, tool... -
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SSD in PyTorch 1.0
High quality, fast, modular reference implementation of SSD in PyTorch
This repository implements SSD (Single Shot MultiBox Detector). The implementation is heavily influenced by the projects ssd.pytorch, pytorch-ssd and maskrcnn-benchmark. This repository aims to be the code base for research based on SSD. Multi-GPU training and inference: We use DistributedDataParallel, you can train or test with arbitrary GPU(s), the training schema will change accordingly. Add your own modules without pain. We abstract backbone, Detector, BoxHead, BoxPredictor, etc. You can... -
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PromptTools
Open-source tools for prompt testing and experimentation
Welcome to prompttools created by Hegel AI! This repo offers a set of open-source, self-hostable tools for experimenting with, testing, and evaluating LLMs, vector databases, and prompts. The core idea is to enable developers to evaluate using familiar interfaces like code, notebooks, and a local playground. -
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Geographical Adventures
Geography game about delivering packages
Geographical Adventures is a collection of projects and experiments focused on procedural generation and geographic simulation, showcasing how complex environments can be created through code. It includes implementations of terrain generation, map systems, and spatial algorithms that simulate real-world geographical features. The project is designed as both a learning resource and a demonstration of procedural techniques, allowing users to explore how landscapes and environments can be generated algorithmically. ... -
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BackgroundMattingV2
Real-Time High-Resolution Background Matting
Official repository for the paper Real-Time High-Resolution Background Matting. Our model requires capturing an additional background image and produces state-of-the-art matting results at 4K 30fps and HD 60fps on an Nvidia RTX 2080 TI GPU. -
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ADAMS
ADAMS is a workflow engine for building complex knowledge workflows.
...Instead of placing operators on a canvas and manually connecting them, a tree structure and flow control operators determine how data is processed (sequentially/parallel). This allows rapid development and easy maintenance of large workflows, with hundreds or thousands of operators. Operators include machine learning (WEKA, MOA, MEKA) and image processing (ImageJ, JAI, BoofCV, LIRE and Gnuplot). R available using Rserve. WEKA webservice allows other frameworks to use WEKA models. Fast prototyping with Groovy and Jython. Read/write support for various databases and spreadsheet applications. -
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irixjoker-sensing-utils
sensing in IRIX emulator lib
Uses machine learning to compute with genetic programming for emulators. -
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MMDeploy
OpenMMLab Model Deployment Framework
MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN...
