Search Results for "deep" - Page 2
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Showing 150 open source projects for "deep"
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Python Outlier Detection
A Python toolbox for scalable outlier detection
PyOD is a comprehensive and scalable Python toolkit for detecting outlying objects in multivariate data. This exciting yet challenging field is commonly referred as outlier detection or anomaly detection. PyOD includes more than 30 detection algorithms, from classical LOF (SIGMOD 2000) to the latest COPOD (ICDM 2020) and SUOD (MLSys 2021). Since 2017, PyOD [AZNL19] has been successfully used in numerous academic researches and commercial products [AZHC+21, AZNHL19]. PyOD has multiple neural... -
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Face Alignment
2D and 3D Face alignment library build using pytorch
Detect facial landmarks from Python using the world's most accurate face alignment network, capable of detecting points in both 2D and 3D coordinates. Build using FAN's state-of-the-art deep learning-based face alignment method. For numerical evaluations, it is highly recommended to use the lua version which uses identical models with the ones evaluated in the paper. More models will be added soon. By default, the package will use the SFD face detector. However, the users can alternatively use dlib, BlazeFace, or pre-existing ground truth bounding boxes. ... -
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Pyro
Deep universal probabilistic programming with Python and PyTorch
Pyro is a flexible, universal probabilistic programming language (PPL) built on PyTorch. It allows for expressive deep probabilistic modeling, combining the best of modern deep learning and Bayesian modeling. Pyro is centered on four main principles: Universal, Scalable, Minimal and Flexible. Pyro is universal in that it can represent any computable probability distribution. It scales easily to large datasets with minimal overhead, and has a small yet powerful core of composable abstractions that make it both agile and maintainable. ... -
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SageMaker Hugging Face Inference Toolkit
Library for serving Transformers models on Amazon SageMaker
...It utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. For the Dockerfiles used for building SageMaker Hugging Face Containers, see AWS Deep Learning Containers. The SageMaker Hugging Face Inference Toolkit implements various additional environment variables to simplify your deployment experience. The Hugging Face Inference Toolkit allows user to override the default methods of the HuggingFaceHandlerService. SageMaker Hugging Face Inference Toolkit is licensed under the Apache 2.0 License. -
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iCSS
More than CSS
iCSS is a large curated repository of advanced CSS techniques, creative experiments, and deep dives into modern web animation and styling capabilities. Rather than being a traditional library, the project functions as an educational and inspirational knowledge base that explores unusual, powerful, or overlooked CSS features. The content covers topics such as layout tricks, animation patterns, visual effects, accessibility considerations, and emerging CSS standards. -
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Synapse Machine Learning
Simple and distributed Machine Learning
SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. SynapseML builds on Apache Spark and SparkML to enable new kinds of machine learning, analytics, and model deployment workflows. SynapseML adds many deep learning and data science tools to the Spark ecosystem, including seamless integration of Spark Machine Learning pipelines with the Open Neural Network Exchange (ONNX), LightGBM, The Cognitive Services, Vowpal Wabbit, and OpenCV. These tools enable powerful and highly-scalable predictive and analytical models for a variety of data sources. ... -
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Underscore.js
JavaScript's utility belt
...Instead of extending built-in objects or modifying prototypes, Underscore provides its helpers in a single _ namespace, enabling cross-browser support and consistent behaviour across environments. It offers map/filter/reduce, deep-cloning, templating, object traversal, function binding, and more, which makes it easier to write concise, expressive code rather than verbose loops and conditional logic. Many other libraries and frameworks (including Backbone) historically depended on or partnered with Underscore for their utility functions. Even though ES6+ and Lodash have overshadowed some of its role, Underscore remains influential and educational for how to design utility APIs. -
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ArkType
TypeScript's 1:1 validator, optimized from editor to runtime
ArkType is a high-performance runtime type validation library for TypeScript. It offers a 1:1 validator optimized from editor to runtime, enabling developers to define and enforce complex type constraints seamlessly. -
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Recommenders 2023
Best Practices on Recommendation Systems
Recommenders objective is to assist researchers, developers and enthusiasts in prototyping, experimenting with and bringing to production a range of classic and state-of-the-art recommendation systems. Recommenders is a project under the Linux Foundation of AI and Data. -
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Lets-Plot
Multiplatform plotting library based on Grammar of Graphics
Lets-Plot is a multiplatform plotting library based on the Grammar of Graphics. The library' design is heavily influenced by Leland Wilkinson work The Grammar of Graphics describing the deep features that underlie all statistical graphics. -
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OCaml
The core OCaml system: compilers, runtime system, base libraries
...The other is a native code compiler that produces more efficient machine code; its performance matches the highest standards of modern compilers. OCaml has great support for the most popular editors. VS Code is recommended for beginners, and for power users there is deep integration with Vim and Emacs. OCaml has a rich and dynamic community and best-in-class tooling. -
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Perfetto
Production-grade client-side tracing, profiling, and analysis
...Perfetto’s ecosystem includes a web-based UI that can load multi-GB traces directly in the browser and an offline “trace processor” that exposes the trace as a queryable SQL-like table schema for deep analysis and automation. It integrates natively with Android (replacing older atrace/Systrace paths) and can sit alongside custom instrumentation in apps or services through its SDKs. -
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Glide
Android image loading & caching library focused on smooth scrolling
...It is primarily focused on making any type of a list of images as smooth and fast as possible, and is able to achieve this through smart and automatic downsampling and caching, aggressive re-use of resources and deep lifecycle integration. Apart from smooth and speedy scrolling, it’s also good for any case where fetching, resizing, and displaying of a remote image is needed. -
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YOLOv9
Learning What You Want to Learn Using Programmable Gradient Info
YOLOv9 is the official implementation of the paper “YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information.” It is a modern object detection repository focused on improving how deep networks preserve useful information during training. The project introduces Programmable Gradient Information and the GELAN architecture to improve gradient flow, parameter efficiency, and train-from-scratch performance. It provides scripts and model assets for training, testing, and running inference on detection tasks. YOLOv9 is designed for real-time detection scenarios where both accuracy and efficiency matter. ... -
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React Router
Declarative routing for React
React Router is a standards‑focused, multi‑strategy routing library for React applications, offering both full‑framework capabilities and lightweight, flexible library usage. It enables robust routing experiences across React versions. It supports advanced features in React 19. You can use it maximally as a React framework or minimally as a library with your own architecture. First‑class type safety with automatic type generation for route params and data. It is designed to facilitate... -
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Antigravity Awesome Skills
The Ultimate Collection of 700+ Agentic Skills for Claude Code
...The project includes skill definitions, example prompts, and usage patterns that highlight how modular abilities can be assembled into functioning assistants. Because it aims to reduce cognitive overhead, many skills show how to structure intents, handle context, and orchestrate multi-step reasoning without deep technical complexity. It also serves as inspiration for users looking to prototype new use cases — from conversational helpers that answer questions to workflow automators that trigger actions. -
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Helium
Lighter web automation with Python
...It replaces verbose boilerplate code with natural language-like API calls such as click("Login") or write("hello", into="Name"). Helium manages browser setup, waits, and teardown, enabling quick development of scripts for testing, scraping, or task automation without requiring deep Selenium knowledge. -
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Impacket
A collection of Python classes for working with network protocols
...It features several protocols, including Ethernet, IP, TCP, UDP, ICMP, IGMP, ARP, NMB and SMB1, SMB2 and SMB3 and more. Impacket's object oriented API makes it easy to work with deep hierarchies of protocols. It can construct packets from scratch, as well as parse them from raw data. -
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Saeba's Blog
Where Saeba writes his blog, he plans to write four series: JavaScript
...Rather than being a software package, it functions as a structured educational repository for developers who want to understand how JavaScript features work under the hood. Many articles focus on concepts such as execution context, scope, prototypes, closures, debounce, throttle, deep copy, currying, and implementation patterns inspired by popular libraries. The repository is useful for self-study, interview preparation, and deeper frontend fundamentals. Its long-running popularity comes from explaining difficult concepts in a systematic and practical way. -
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Compose Destinations
Annotation processing library for type-safe Jetpack Compose navigation
A KSP library that processes annotations and generates code that uses Official Jetpack Compose Navigation under the hood. It hides the complex, non-type-safe and boilerplate code you would have to write otherwise. No need to learn a whole new framework to navigate - most APIs are either the same as with the Jetpack Components or inspired by them. -
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Theseus
A library for differentiable nonlinear optimization
...Helper packages provide geometry primitives and utilities for composing priors, relative constraints, and measurement models. Theseus bridges the gap between classical optimization and deep learning, enabling hybrid systems that learn components. -
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Tile Kernels
A kernel library written in tilelang
...TileKernels also includes testing and benchmarking utilities to help evaluate correctness and performance. Its main value is providing reusable TileLang-based kernels for experimental and production-adjacent deep-learning systems. -
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Machine Learning Tutorials Repository
Dive deep into the realms of Machine Learning and other topics
The Machine Learning Tutorials Repository is a comprehensive collection of resources, examples, and implementations designed to help users understand and apply machine learning concepts. It covers a wide range of topics, including supervised learning, unsupervised learning, neural networks, and data preprocessing techniques. The project is structured to provide both theoretical explanations and practical code examples, making it suitable for learners at different levels. It includes... -
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Integrant
Micro-framework for data-driven architecture
Integrant is a minimalistic micro-framework for building applications following a data-driven architecture. It lets you define system components declaratively as configuration data and handles lifecycle actions (init, halt, resume) in dependency order, serving as a modern alternative to Component or Mount. Integrant was built as a reaction to fix some perceived weaknesses with Component. In Component, systems are created programmatically. Constructor functions are used to build records,... -
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Shumai
Fast Differentiable Tensor Library in JavaScript & TypeScript with Bun
...Built on Bun and Flashlight, with ArrayFire as its numerical backend, Shumai brings GPU-accelerated tensor operations, automatic differentiation, and scientific computing tools directly to JavaScript developers. It allows seamless integration of machine learning, deep learning, and custom differentiable programs into web-based or server-side environments without relying on Python frameworks. The library supports matrix operations, gradient computation, and tensor conversions with intuitive APIs and near-native speed, thanks to Bun’s low-overhead FFI bindings. It can automatically leverage GPU acceleration on Linux (via CUDA) and CPU computation on macOS.
