Showing 10 open source projects for "ai programming"

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    Vibe Coding CN

    Vibe Coding CN

    The ultimate workstation for turning ideas into reality

    vibe-coding-cn is an open-source guide and resource collection for AI-assisted software development. It presents a workflow for turning ideas into working projects through structured AI pair programming. The methodology emphasizes planning, modular architecture, clear goals, strong context, and human review instead of uncontrolled AI generation. It covers project conception, technology selection, implementation, debugging, testing, and expansion.
    Downloads: 0 This Week
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  • 2
    Claude Cookbooks

    Claude Cookbooks

    A collection of notebooks/recipes showcasing ways of using Claude

    Claude Cookbooks is a curated collection of practical examples, notebooks, and implementation guides that demonstrate how to effectively use Claude’s API across a wide range of tasks. It serves as both a learning resource and a reference library, helping developers understand how to apply AI capabilities such as classification, summarization, and retrieval-augmented generation in real-world scenarios. The repository includes structured examples for integrating Claude with external tools,...
    Downloads: 2 This Week
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  • 3
    A to Z Resources for Students

    A to Z Resources for Students

    Curated list of resources for developers

    A to Z Resources for Students is a curated directory of learning materials, developer tools, programs, events, and career opportunities for students and early-career technologists. It helps users discover resources for learning programming languages, frameworks, AI, machine learning, cybersecurity, mobile development, and other technical fields. The collection also includes hackathons, competitions, internships, student programs, open-source opportunities, and networking communities. Interview preparation and free developer resources are organized alongside educational links. ...
    Downloads: 0 This Week
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  • 4
    CS Fundamentals

    CS Fundamentals

    Curated CS fundamentals for placement prep

    ...It gathers notes, PDFs, cheat sheets, question banks, and roadmaps across major CS subjects. The collection covers data structures and algorithms, computer networks, DBMS and SQL, object-oriented programming, operating systems, software engineering, and system design. It also includes general job-preparation material such as HR interview questions, LeetCode resources, cover letter material, off-campus hiring references, and AI prompts for interview practice. The project is organized by subject folders so learners can quickly jump into a specific topic. ...
    Downloads: 3 This Week
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    TensorRT

    TensorRT

    C++ library for high performance inference on NVIDIA GPUs

    NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference. It includes a deep learning inference optimizer and runtime that delivers low latency and high throughput for deep learning inference applications. TensorRT-based applications perform up to 40X faster than CPU-only platforms during inference. With TensorRT, you can optimize neural network models trained in all major frameworks, calibrate for lower precision with high accuracy, and deploy to hyperscale data centers,...
    Downloads: 3 This Week
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  • 6

    Proteus Model Builder

    GUI for training of neural network models for GuitarML Proteus

    ...GuitarML's work on Proteus, NeuralPi and Proteusboard (hardware) is amazing. https://github.com/GuitarML Yet, it is not easy to wrap your head around if you are not familiar with programming, AI, machine learning, neuronal networks. So, Keith Bloemer a.k.a. GuitarML set up a Google Colab script to give people the Opportunity to train their own models online. Still, I thought that things could be easier, and I wanted a faster way to work with the python scripts. So I automated some things on my Windows 10 machine. ...
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    Downloads: 51 This Week
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  • 7
    roadmap.sh

    roadmap.sh

    Interactive roadmaps, guides and other educational content

    roadmap.sh is the content repository behind roadmap.sh, a community-driven platform for structured technology and career learning paths. It contains interactive roadmaps covering roles, programming languages, frameworks, infrastructure, databases, AI, security, and engineering practices. Each roadmap is divided into topics that link to concise explanations and selected learning resources. The repository also includes best-practice guides and question sets for testing knowledge in areas such as frontend, backend, React, and Node.js. ...
    Downloads: 1 This Week
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  • 8
    Julia.jl

    Julia.jl

    Curated decibans of Julia programming language

    Julia.jl is a curated collection of knowledge resources for the Julia programming language, designed to support high-performance numerical analysis and computational science. The repository aggregates diverse content across domains such as mathematics, physics, data science, optimization, machine learning, and supercomputing. It functions as a structured index, helping developers, researchers, and learners easily find materials to deepen their understanding of Julia’s ecosystem. The project...
    Downloads: 0 This Week
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  • 9
    Pythonidae

    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,...
    Downloads: 3 This Week
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  • 10
    Functional, Data Science Intro To Python

    Functional, Data Science Intro To Python

    [tutorial]A functional, Data Science focused introduction to Python

    The first section is an intentionally brief, functional, data science-centric introduction to Python. The assumption is a someone with zero experience in programming can follow this tutorial and learn Python with the smallest amount of information possible. The sections after that, involve varying levels of difficulty and cover topics as diverse as Machine Learning, Linear Optimization, build systems, command line tools, recommendation engines, Sentiment Analysis and Cloud Computing.
    Downloads: 0 This Week
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