Search Results for "programming" - Page 5
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Showing 430 open source projects for "programming"
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Defang
Defang CLI and sample projects
...By leveraging AI-assisted tooling, Defang enables developers to swiftly transition from an idea to a deployed application on their preferred cloud provider. The platform supports multiple programming languages, including Go, JavaScript, and Python, allowing developers to start with sample projects or generate project outlines using natural language prompts. With a single command, Defang builds and deploys applications, handling configurations for computing, storage, load balancing, networking, logging, and security. The Defang Command Line Interface (CLI) facilitates interactions with the platform, offering installation options via shell scripts, Homebrew, Winget, Nix, or direct download. ... -
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TorchCode
Practice implementing softmax, attention, GPT-2 and more
TorchCode is an interactive learning and practice platform designed to help developers master PyTorch by implementing core machine learning operations and architectures from scratch. It is structured similarly to competitive programming platforms like LeetCode but focuses specifically on tensor operations and deep learning concepts. The platform provides a collection of curated problems that cover fundamental topics such as activation functions, normalization layers, attention mechanisms, and full transformer architectures. It runs in a Jupyter-based environment, allowing users to write, test, and debug their code interactively while receiving immediate feedback. ... -
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Modular Platform
The Modular Platform (includes MAX & Mojo)
...The project centers on enabling developers to run AI models faster and more efficiently by rethinking the traditional ML software stack. It is closely associated with the Mojo programming language and related tooling that aims to combine Python usability with systems-level performance. Modular’s ecosystem is designed to simplify deployment of AI workloads across heterogeneous hardware while maximizing throughput. The repository reflects an effort to modernize the AI development pipeline from compilation to runtime execution. ... -
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React Native ExecuTorch
Declarative way to run AI models in React Native on device
...The project supports a range of AI use cases, including large language models, computer vision, OCR, object detection, speech processing, segmentation, and embeddings. It helps React Native developers use local AI capabilities without needing deep native programming or machine learning infrastructure expertise. The library is especially relevant for privacy-first apps, offline experiences, and mobile products that need low-latency inference. Its main value is bridging React Native with native AI execution so apps can run powerful models directly on user devices. -
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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thorough-pytorch
PyTorch Getting Started Tutorial, read online
...The project encourages collaborative learning and often organizes materials in a step-by-step progression that gradually increases in complexity. Topics include neural network fundamentals, training procedures, model evaluation, and practical deep learning workflows. By combining structured lessons with programming projects, the repository aims to help learners develop both conceptual understanding and practical implementation skills. -
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Useful Java links
A list of useful Java frameworks, libraries, software and hello worlds
Useful Java links repository is a curated collection of educational resources, frameworks, tools, and documentation related to Java programming and the broader Java ecosystem. The project organizes hundreds of links to libraries, development frameworks, tutorials, and technical references that are useful for both beginner and advanced Java developers. These resources cover many areas of software development, including web frameworks, testing libraries, concurrency tools, build systems, microservices architectures, and development best practices. ... -
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machine_learning_examples
A collection of machine learning examples and tutorials
machine_learning_examples is an open-source repository that provides a large collection of machine learning tutorials and practical code examples. The project aims to teach machine learning concepts through hands-on programming rather than purely theoretical explanations. It includes implementations of many machine learning algorithms and neural network architectures using Python and popular libraries such as TensorFlow and NumPy. The repository covers a wide range of topics including supervised learning, unsupervised learning, reinforcement learning, and natural language processing. ... -
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MathModelAgent
An Agent Designed for Mathematical Modeling
...The platform automates the process of analyzing mathematical problems, constructing models, generating code for simulations or computations, and producing a complete research-style report. The project uses a multi-agent architecture where different specialized agents handle tasks such as problem interpretation, modeling design, programming implementation, and paper writing. Through integration with multiple large language models, the system can coordinate these components to generate structured modeling solutions and formatted research papers suitable for submission. The platform also includes a code execution environment that allows generated programs to be tested, corrected, and refined during the modeling workflow. -
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i.am.ai
Roadmap to becoming an Artificial Intelligence Expert in 2022
...It was originally created to train internal employees but was released publicly to support the broader community. The roadmap emphasizes foundational skills like mathematics, programming, and data handling before progressing into deep learning and specialized domains. Rather than prescribing a single path, it helps users navigate the AI landscape and understand which tools fit different scenarios. Overall, the repository serves as a high-level strategic learning map for individuals planning long-term AI careers. -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Shire
Empower Your Dev Ecosystem with AI Agents
Shire is an AI-driven development ecosystem that empowers developers with AI agents to automate coding tasks, enhance productivity, and elevate code quality. The concept of Shire has its roots in AutoDev, a subproject of UnitMesh. Within AutoDev, we envisioned an AI-driven integrated development environment for developers, which included Shire’s predecessor, DevIns. DevIns was designed to empower users to create custom AI agents tailored to their own IDEs, thus forging a personalized... -
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Codai
Codai is an AI code assistant that helps developers
Codai is an AI code assistant designed to help developers efficiently manage their daily tasks through a session-based CLI, such as adding new features, refactoring, and performing detailed code reviews. What makes codai stand out is its deep understanding of the entire context of your project, enabling it to analyze your code base and suggest improvements or new code based on your context. This AI-powered tool supports multiple LLM providers, such as OpenAI, Azure OpenAI, Ollama, Anthropic,... -
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Haiku Sonnet for JAX
JAX-based neural network library
...JAX is a numerical computing library that combines NumPy, automatic differentiation, and first-class GPU/TPU support. Haiku is a simple neural network library for JAX that enables users to use familiar object-oriented programming models while allowing full access to JAX's pure function transformations. Haiku provides two core tools: a module abstraction, hk.Module, and a simple function transformation, hk.transform. hk.Modules are Python objects that hold references to their own parameters, other modules, and methods that apply functions on user inputs. hk.transform turns functions that use these object-oriented, functionally "impure" modules into pure functions that can be used with jax.jit, jax.grad, jax.pmap, etc. -
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Angel
A Flexible and Powerful Parameter Server for large-scale ML
Angel is a high-performance distributed machine learning and graph computing platform based on the philosophy of Parameter Server. It is tuned for performance with big data from Tencent and has a wide range of applicability and stability, demonstrating an increasing advantage in handling higher-dimension models. Angel is jointly developed by Tencent and Peking University, taking account of both high availability in industry and innovation in academia. With a model-centered core design... -
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MCP UI
SDK for building interactive UI components over MCP for AI tools
...It includes both client-side and server-side SDKs, making it possible to define UI elements on the backend and handle user interactions on the frontend. It supports multiple programming environments, including TypeScript, Python, and Ruby, broadening its accessibility for developers. -
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Gen.jl
A general-purpose probabilistic programming system
An open-source stack for generative modeling and probabilistic inference. Gen’s inference library gives users building blocks for writing efficient probabilistic inference algorithms that are tailored to their models, while automating the tricky math and the low-level implementation details. Gen helps users write hybrid algorithms that combine neural networks, variational inference, sequential Monte Carlo samplers, and Markov chain Monte Carlo. Gen features an easy-to-use modeling language... -
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Flutter Agent Skills
Agent skills for Flutter, maintained by the Flutter team
...The project focuses on practical learning through guided coding challenges, interactive examples, and real-world mobile application scenarios rather than purely theoretical documentation. It covers topics such as UI construction, state management, animations, asynchronous programming, architecture patterns, and testing workflows within Flutter applications. The repository is designed for developers at different experience levels, offering incremental progression from foundational concepts to more advanced mobile engineering techniques. It emphasizes clean coding practices, reusable components, and modern Flutter development patterns. ... -
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AI Engineering from Scratch
Learn it. Build it. Ship it for others
...Each lesson emphasizes hands-on implementation, requiring learners to write core components such as backpropagation, tokenizers, and attention mechanisms themselves before using higher-level tools. The curriculum spans multiple programming languages, including Python, TypeScript, Rust, and Julia, which broadens the learner’s exposure to different ecosystems and performance considerations. It also focuses on producing tangible outputs such as prompts, agents, and reusable systems, allowing learners to build a real portfolio while studying. -
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AsmJit
Low-latency machine code generation
...It is commonly used in applications such as emulators, compilers, and high-performance computing systems where runtime optimization is essential. asmjit emphasizes low latency and efficiency, ensuring that generated code executes quickly without significant overhead. Its modular design allows developers to integrate it into various systems with minimal friction. Overall, asmjit bridges the gap between high-level programming and low-level execution by enabling efficient runtime code generation. -
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ZML
Any model. Any hardware. Zero compromise
ZML is a high-performance machine learning inference stack designed to run AI models efficiently across heterogeneous hardware environments using a modern systems programming approach. Built with technologies such as Zig, MLIR, and Bazel, it focuses on production-grade deployment where performance, portability, and scalability are critical. The system allows models to be compiled and executed across multiple types of accelerators, including GPUs and TPUs, even when distributed across different machines or locations. ... -
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TypeAgent Python
Structured RAG: ingest, index, query
...Instead of relying solely on free-form prompts, the architecture emphasizes converting natural language interactions into structured representations that can be processed by deterministic software components. This design allows the system to combine the flexibility of language models with the reliability of traditional programming logic. The repository is intended primarily as a research prototype and sample code rather than a production-ready framework, allowing developers to experiment with building AI agents that maintain structured memory and perform tasks through defined actions. -
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Diffrax
Numerical differential equation solvers in JAX
...The project provides tools for solving ordinary differential equations, stochastic differential equations, controlled differential equations, and related systems in a way that fits naturally into modern machine learning and differentiable programming workflows. Because it is written to work closely with JAX, it supports just-in-time compilation, automatic differentiation, vectorization, and accelerator-backed execution on hardware such as GPUs and TPUs. This makes it especially appealing for researchers who need equation solvers that can be embedded inside trainable models or simulation-heavy learning systems. -
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qxresearch-event-1
Python hands on tutorial with 50+ Python Application
qxresearch-event-1 is an open-source educational repository that provides a collection of lightweight Python applications designed to demonstrate programming concepts and artificial intelligence techniques in simple and accessible examples. The repository contains dozens of small programs, many implemented with minimal lines of code, covering topics such as machine learning, graphical user interfaces, computer vision, and API integration. Each example is designed to illustrate a single concept or application in a clear and concise manner so that learners can quickly understand the underlying logic. ... -
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Deepnote
Deepnote is a drop-in replacement for Jupyter
...Built on top of the Jupyter kernel ecosystem, it maintains compatibility with existing notebook workflows while introducing additional features focused on collaboration and automation. The system supports programming languages such as Python, R, and SQL and allows users to execute and analyze data directly within interactive notebooks. Deepnote emphasizes team-based data science by enabling real-time collaboration similar to shared document editors, allowing multiple users to work simultaneously on the same notebook environment. -
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Data Science Interviews
Data science interview questions and answers
...The project serves as a preparation resource for students, job seekers, and professionals who want to review the technical knowledge required for data science roles. The repository organizes questions into different categories including theoretical machine learning concepts, technical programming questions, and probability or statistics problems. Many of the questions cover fundamental machine learning topics such as linear models, decision trees, neural networks, and evaluation metrics. In addition to theoretical questions, the repository also includes practical interview topics related to coding challenges, SQL queries, and algorithmic thinking. -
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Floneum
Instant, controllable, local pre-trained AI models in Rust
...Floneum supports a plugin architecture that allows external components to extend the platform while maintaining isolation and security. Many plugins can be written in different programming languages and compiled to WebAssembly modules, allowing them to run safely within the system. The platform is implemented primarily in Rust and emphasizes performance, modularity, and local execution.
