Search Results for "deep" - Page 2
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Showing 123 open source projects for "deep"
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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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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. -
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XNNPACK
High-efficiency floating-point neural network inference operators
XNNPACK is a highly optimized, low-level neural network inference library developed by Google for accelerating deep learning workloads across a variety of hardware architectures, including ARM, x86, WebAssembly, and RISC-V. Rather than serving as a standalone ML framework, XNNPACK provides high-performance computational primitives—such as convolutions, pooling, activation functions, and arithmetic operations—that are integrated into higher-level frameworks like TensorFlow Lite, PyTorch Mobile, ONNX Runtime, TensorFlow.js, and MediaPipe. ... -
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Awesome English Ebooks
Curated list of freely available English-language magazine issues
awesome-english-ebooks is a curated list that collects high-quality, English-language ebooks across programming, computer science, mathematics, and related technical domains. The repository organizes links by topic and technology so learners can quickly find foundational texts, deep dives, and practical handbooks relevant to their goals. Entries often include notes about edition, format, or prerequisite knowledge, helping readers gauge where a book fits in a learning path. Because it lives in Git, the list benefits from community maintenance: contributors add new titles, replace dead links, and refine categories as the ecosystem shifts. ... -
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libsodium.js
libsodium compiled to Webassembly and pure JavaScript
...It exposes a comprehensive set of APIs for encryption, decryption, hashing, digital signatures, and key exchange, all designed to be safe and easy to use without requiring deep cryptographic expertise. The library leverages WebAssembly for improved performance, enabling near-native execution speeds within browsers and JavaScript runtimes. It is designed to prevent common cryptographic mistakes by offering secure defaults and abstractions that reduce the risk of misuse. libsodium.js is particularly useful for building secure web applications, messaging systems, and privacy-focused tools that require client-side encryption. ... -
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ArgoSBX
Xiaobai built his own agent artifact
...One of its defining features is the ability to integrate CDN-based routing and WARP combinations, offering numerous configuration permutations to optimize performance and bypass restrictions. The script is built for minimal interaction, allowing users to deploy complex setups with a single command while still retaining deep customization options. -
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Karpathy-Inspired Claude Code Guidelines
A single CLAUDE.md file to improve Claude Code behavior
Karpathy-Inspired Claude Code Guidelines is a curated learning and experimentation repository inspired by the work and teaching philosophy of Andrej Karpathy, designed to help learners build practical competence in deep learning, neural networks, and AI infrastructure. The project organizes a progressive path through exercises, notebooks, code examples, and practical mini-projects that echo Karpathy’s approach to “learning by doing,” where students build core concepts from first principles rather than consuming superficial abstractions. It covers topics like implementing backpropagation from scratch, understanding convolutional and recurrent networks, building simple training loops, and exploring real datasets with hands-on code. ... -
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zshy
Bundler-free build tool for TypeScript libraries
...Instead of relying on bundlers like Webpack or tsup, zshy leverages the TypeScript compiler (tsc) itself to produce both ESM and CommonJS builds, generate type declarations, and automatically populate "exports" fields in a package’s package.json. It reads configuration directly from package.json and standard TypeScript config files, doesn’t require its own config, and supports multi-entry libraries with deep wildcard exports. Originally created for building popular libraries such as Zod, zshy fills the niche for a straightforward, convention-over-configuration build pipeline for TypeScript packages. The tool copies non-JS assets, supports .tsx, and makes CLI packaging easy, helping maintain consistent library outputs with minimal boilerplate.
