Showing 9 open source projects for "ex4/ex5 to source code"

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    AutoResearchClaw

    AutoResearchClaw

    Autonomous research from idea to paper. Chat an Idea. Get a Paper 🦞

    AutoResearchClaw is an open-source framework designed to automatically generate full academic research papers from a single idea or topic. Built in Python, it orchestrates a multi-stage research pipeline that gathers literature, formulates hypotheses, runs experiments, analyzes results, and writes the final paper. The system retrieves real academic references from sources such as arXiv and Semantic Scholar to ensure credible citations.
    Downloads: 3 This Week
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  • 2
    nanoGPT

    nanoGPT

    The simplest, fastest repository for training/finetuning models

    NanoGPT is a minimalistic yet powerful reimplementation of GPT-style transformers created by Andrej Karpathy for educational and research use. It distills the GPT architecture into a few hundred lines of Python code, making it far easier to understand than large, production-scale implementations. The repo is organized with a training pipeline (dataset preprocessing, model definition, optimizer, training loop) and inference script so you can train a small GPT on text datasets like Shakespeare...
    Downloads: 2 This Week
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  • 3
    AI Researcher

    AI Researcher

    An autonomous AI researcher

    AI Researcher is an experimental open-source project that demonstrates how multiple AI agents can collaborate to conduct complex research tasks from start to finish with minimal human intervention. It orchestrates agents that can generate research questions, perform literature reviews, execute experiments, analyze results, and synthesize findings into structured outputs like reports or code.
    Downloads: 4 This Week
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  • 4
    Growth Lab

    Growth Lab

    An end-to-end growth tool that understands the product

    Growth Lab is an open-source agentic growth workspace that connects product understanding, market research, execution, measurement, and iteration. It uses Codex or Claude Code as the runtime and treats natural-language conversations as the control surface. Collectors gather product, market, content, and channel evidence, while executor skills help create, publish, review, and coordinate growth work.
    Downloads: 0 This Week
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    Paessler - Monitor Your Whole Network in Minutes

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  • 5
    Brain Tokyo Workshop

    Brain Tokyo Workshop

    Experiments and code from Google Brain’s Tokyo research workshop

    The Brain Tokyo Workshop repository hosts a collection of research materials and experimental code developed by the Google Brain team based in Tokyo. It showcases a variety of cutting-edge projects in artificial intelligence, particularly in the areas of neuroevolution, reinforcement learning, and model interpretability. Each project explores innovative approaches to learning, prediction, and creativity in neural networks, often through unconventional or biologically inspired methods. The...
    Downloads: 0 This Week
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  • 6
    Catalyst

    Catalyst

    Accelerated deep learning R&D

    Catalyst is a PyTorch framework for accelerated Deep Learning research and development. It allows you to write compact but full-featured Deep Learning pipelines with just a few lines of code. With Catalyst you get a full set of features including a training loop with metrics, model checkpointing and more, all without the boilerplate. Catalyst is focused on reproducibility, rapid experimentation, and codebase reuse so you can break the cycle of writing another regular train loop and make...
    Downloads: 0 This Week
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  • 7
    ...Installation Videos! Part 1: http://youtu.be/rnv2VLcG-eI Part 2: http://youtu.be/eFudbMWHNlQ Special thanks to Wells Oliver for the code for downloading Retrosheet files. And the Chadwick project for its Retrosheet tools. https://sourceforge.net/projects/chadwick/?source=recommended
    Downloads: 0 This Week
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  • 8
    Pydicom by examples

    Pydicom by examples

    Basic and intermediate examples of DICOM library with Jupyter

    Basic and intermediate examples to read, modify and write DICOM files with Python code using Jupyter - To install Jupyter - https://jupyter.org/install ====== All examples are based on Pydicom. An open source library - https://pydicom.github.io/
    Downloads: 0 This Week
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  • 9
    Make AsciiDoc part of your literate programming tool set. With eWEB you can weave and tangle literate programs written as AsciiDoc documents, using embedded WEB code snippets.
    Downloads: 0 This Week
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