Search Results for "machine learning projects" - Page 57
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Showing 2393 open source projects for "machine learning projects"
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node-elm
Backend system based on node.js + Mongodb
node-elm is a Node.js back end that powers the data side of the Ele.me clone ecosystem, complementing the Vue front-end projects. It exposes RESTful endpoints for entities such as restaurants, menus, orders, users, and addresses to simulate a realistic delivery stack. The server demonstrates how to structure a project with routing, controllers, and middleware to keep logic testable and readable. It typically includes authentication flows, input validation, and error handling that mirror... -
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Ferret
Ferret is a web scraping system
Ferret is a web scraping system. It aims to simplify data extraction from the web for UI testing, machine learning, analytics and more. ferret allows users to focus on the data. It abstracts away the technical details and complexity of underlying technologies using its own declarative language. It is extremely portable, extensible, and fast. -
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Scikit-Optimize
Sequential model-based optimization with a `scipy.optimize` interface
Scikit-Optimize, or skopt, is a simple and efficient library to minimize (very) expensive and noisy black-box functions. It implements several methods for sequential model-based optimization. skopt aims to be accessible and easy to use in many contexts. The library is built on top of NumPy, SciPy and Scikit-Learn. -
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Advanced CSS Course
Starter files, final projects and FAQ for my Advanced CSS course
Advanced CSS Course is the official course-material repository for Jonas Schmedtmann’s Advanced CSS and Sass course. It contains starter files and finished project files for the projects taught throughout the course, giving learners a structured way to code along and compare their work with the completed versions. The repository focuses on modern CSS techniques such as Sass, responsive layouts, animations, Flexbox, CSS Grid, and reusable design patterns. It also includes downloadable course slides, making it easier to follow the theory portions alongside the hands-on projects. ... -
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.
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TensorFlow Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
TensorFlow Examples is a comprehensive repository of example implementations, tutorials, and reference code intended to help newcomers and intermediate learners dive into TensorFlow quickly. It contains both Jupyter notebooks and raw source code, covering a broad range of tasks: from basic machine-learning and neural-network models to more advanced use cases, using both TensorFlow v1 and v2 APIs. For clarity and educational value, each example is accompanied by explanatory comments or markdown cells to illustrate what the code does and why — a design that makes it especially suitable for self-learners or students following along with real data. ... -
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Detectron2
Next-generation platform for object detection and segmentation
Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark. It is powered by the PyTorch deep learning framework. Includes more features such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, etc. Can be used as a library to support different projects on top of it. We'll open source more research projects in this way. It trains much faster. Models can be exported to TorchScript format or Caffe2 format for deployment. ... -
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Arxiv Sanity Preserver
Web interface for browsing, search and filtering arxiv submissions
Arxiv Sanity Preserver is a web application for discovering, organizing, and filtering machine-learning research papers from arXiv. It was created to make the large daily flow of new submissions easier for researchers to manage. The backend downloads papers, extracts their text, creates thumbnails, and computes TF-IDF representations for similarity analysis. Users can search papers, find work similar to a selected paper, browse popular submissions, and maintain a personal library. ... -
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YOLOv4
PyTorch implementation of YOLOv4
...The repository supports common detection workflows such as dataset preparation, model training, evaluation, inference, and weight conversion. It is useful for developers who prefer the PyTorch ecosystem for experimentation, debugging, and integration with other machine learning tooling. The project also connects to the broader YOLOv4 family, including CSP-based architecture ideas and real-time detection improvements. It is best suited for researchers and engineers who want YOLOv4 behavior in a Python-first deep learning environment. -
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SciMLTutorials.jl
Tutorials for doing scientific machine learning (SciML)
SciMLTutorials.jl holds PDFs, webpages, and interactive Jupyter notebooks showing how to utilize the software in the SciML Scientific Machine Learning ecosystem. This set of tutorials was made to complement the documentation and the devdocs by providing practical examples of the concepts. For more details, please consult the docs. To view the SciML Tutorials, go to tutorials.sciml.ai. By default, this will lead to the latest tagged version of the tutorials -
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AI-for-Security-Learning
AI-based security algorithms, and security data analysis
AI-for-Security-Learning is an educational repository that explores the intersection of artificial intelligence and cybersecurity. The project compiles learning resources, examples, and experimental tools that demonstrate how machine learning techniques can be applied to security-related problems. Topics addressed in the repository include malware detection, anomaly detection, threat classification, and intrusion detection systems. -
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Machine Learning Collection
A resource for learning about Machine learning & Deep Learning
A resource for learning about Machine learning & Deep Learning. In this repository, you will find tutorials and projects related to Machine Learning. I try to make the code as clear as possible, and the goal is be to used as a learning resource and a way to look up problems to solve specific problems. For most, I have also done video explanations on YouTube if you want a walkthrough for the code. -
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MTBook
Machine Translation: Foundations and Models
This is a tutorial, the purpose is to introduce the basic knowledge and modeling methods of machine translation systematically, and on this basis, discuss some cutting-edge technologies of machine translation (formerly known as "Machine Translation: Statistical Modeling and Deep Learning") method"). Its content is compiled into a book, which can be used for the study of senior undergraduates and graduate students in computer and artificial intelligence related majors, and can also be used as reference material for researchers related to natural language processing, especially machine translation. ... -
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TorchGAN
Research Framework for easy and efficient training of GANs
The torchgan package consists of various generative adversarial networks and utilities that have been found useful in training them. This package provides an easy-to-use API which can be used to train popular GANs as well as develop newer variants. The core idea behind this project is to facilitate easy and rapid generative adversarial model research. TorchGAN is a Pytorch-based framework for designing and developing Generative Adversarial Networks. This framework has been designed to... -
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Graphics Workshop
Learn computer graphics by writing GPU shaders
Graphics Workshop is an educational computer graphics repository built around writing GPU shaders. It teaches graphics concepts through interactive two-dimensional and three-dimensional browser projects. The workshop covers topics such as fragment shaders, procedural textures, rasterization, lighting, stylized rendering, and real-time ray tracing. It is designed so learners can focus on shader code while the surrounding WebGL and JavaScript harness is already provided. Projects are meant to... -
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SparrowRecSys
A Deep Learning Recommender System
SparrowRecSys is an open-source deep learning recommendation system framework designed to demonstrate the architecture and implementation of modern industrial-scale recommender systems. The project integrates multiple machine learning models and data processing pipelines to simulate how real-world recommendation platforms operate. It includes components for offline data processing, feature engineering, model training, real-time data updates, and online recommendation services. ... -
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Sklearn TensorFlow
Sklearn and TensorFlow: A Practical Guide to Machine Learning
...It focuses on teaching core machine learning concepts using Python while demonstrating practical workflows with popular libraries like Scikit-Learn and TensorFlow. The material covers topics ranging from basic machine learning theory to deep learning techniques and model evaluation, enabling learners to build and experiment with models step by step. -
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Deep-Learning-with-TensorFlow-book
Open source Deep Learning book, based on TensorFlow
Deep-Learning-with-TensorFlow-book is an open-source deep learning book based on TensorFlow 2.0. It combines theory with practical examples, making it suitable for beginners who want to learn deep learning through hands-on code. The repository includes the PDF book, companion source code, course slides, and notebook-style materials. It covers core machine learning and deep learning concepts through TensorFlow-based implementation. -
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VoiceFixer
General Speech Restoration
VoiceFixer is a machine-learning framework for “speech restoration”: given a degraded or distorted audio recording — with noise, clipping, low sampling rate, reverberation, or other artifacts — it attempts to recover high-fidelity, clean speech. The architecture works in two stages: first an analysis stage that tries to extract “clean” intermediate features from the noisy audio (e.g. removing noise, denoising, dereverberation, upsampling), and then a neural vocoder-based synthesis stage that reconstructs a high-quality waveform from those features. ... -
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Bareflank Hypervisor
lightweight hypervisor SDK written in C++
The Bareflank Hypervisor is an open source hypervisor Software Development Toolkit (SDK) for Rust and C++, led by Assured Information Security, Inc. (AIS), that provides the tools needed to rapidly prototype and create your own hypervisor on 64bit versions of Intel and AMD (ARMv8 CPUs, RISC-V and PowerPC also planned). The Bareflank SDK is intended for instructional/research purposes as it only provides enough virtualization support to start/stop a hypervisor. Bareflank can also be used as... -
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Aquila DB
An easy to use Neural Search Engine
...In other words, it is a database to index Latent Vectors generated by ML models along with JSON Metadata to perform k-NN retrieval. It is dead simple to set up, language-agnostic, and drop in addition to your Machine Learning Applications. Aquila DB, as of current features is a ready solution for Machine Learning engineers and Data scientists to build Neural Information Retrieval applications out of the box with minimal dependencies. -
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Tez
Tez is a super-simple and lightweight Trainer for PyTorch
Tez is a super-simple and lightweight Trainer for PyTorch. It also comes with many utils that you can use to tackle over 90% of deep learning projects in PyTorch. tez (तेज़ / تیز) means sharp, fast & active. This is a simple, to-the-point, library to make your PyTorch training easy. This library is in early-stage currently! So, there might be breaking changes. Currently, tez supports cpu, single gpu and multi-gpu & tpu training. More coming soon! Using tez is super-easy. ... -
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TensorRT Pro
C++ library based on tensorrt integration
High-level interface for C++/Python. Simplify the implementation of the custom plugin. And serialization and deserialization have been encapsulated for easier usage. Simplify the compilation of fp32, fp16 and int8 for facilitating the deployment with C++/Python in server or embedded device. Models ready for use also with examples are RetinaFace, Scrfd, YoloV5, YoloX, Arcface, AlphaPose, CenterNet and DeepSORT(C++). -
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...In addition to spectral similarity measures, Calibr provides other two types of features related to precursor ion and spectrum property and statistics from spectrum-spectrum matches (SSMs) for machine-learning based validation. To support users to conveniently conduct spectral library searching and validation, we have also implemented a GUI application, called CalibrWizard. It integrates Calibr and PercolatorTsvConverter, a conversion tool for converting Calibr's results into a tab-delimited format as input to Percolator, and can use the function of Percolator for validation. ...
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useful-custom-react-hooks
This project was bootstrapped with Create React App
useful-custom-react-hooks is a React learning project that demonstrates a broad collection of reusable custom hooks. It is built as a Create React App project and organizes each hook into its own component example. The repository covers common UI, browser, state, timing, storage, network, and interaction patterns that React developers often rebuild across projects. It includes hooks for toggling state, debouncing values, tracking previous values, managing arrays, storing data, fetching resources, loading scripts, and reacting to browser events. ... -
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Pythonidae
Curated decibans of scientific programming resources in Python
Pythonidae is a curated collection of scientific programming resources in Python, designed to support research and development across a wide range of disciplines. The repository organizes tools and libraries into domain-specific categories, including mathematics, statistics, machine learning, artificial intelligence, biology, chemistry, physics, earth sciences, and supercomputing. It also covers practical areas such as build automation, databases, APIs, computer graphics, and utilities, offering a structured reference for both academic and applied work. While the primary focus is on Python, some entries also highlight resources implemented in other languages like Julia, R, Go, and Java. ...
