Showing 10 open source projects for "python code"

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  • 1
    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. It can automatically generate code for experiments, run them in a sandbox environment, and analyze the results with statistical methods. ...
    Downloads: 33 This Week
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  • 2
    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. Each agent operates with clear roles — such as researcher, analyst, and summarizer — and they...
    Downloads: 0 This Week
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  • 3
    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: 2 This Week
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  • 4
    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 something totally new. Catalyst is compatible with Python 3.6+. ...
    Downloads: 1 This Week
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    Planview is the leading end-to-end platform for Strategic Portfolio Management (SPM) and Digital Product Development (DPD)

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  • 5
    DeepMind Lab

    DeepMind Lab

    A customizable 3D platform for agent-based AI research

    DeepMind Lab is a 3D learning environment based on id Software's Quake III Arena via ioquake3 and other open source software. DeepMind Lab provides a suite of challenging 3D navigation and puzzle-solving tasks for learning agents. Its primary purpose is to act as a testbed for research in artificial intelligence, especially deep reinforcement learning. If you use DeepMind Lab in your research and would like to cite the DeepMind Lab environment, we suggest you cite the DeepMind Lab paper. To...
    Downloads: 1 This Week
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  • 6
    wav2letter++

    wav2letter++

    Facebook AI research's automatic speech recognition toolkit

    ...All results reproduction must use Flashlight <= 0.3.2 for exact reproducibility. At least one of LZMA, BZip2, or Z is required for LM compression with KenLM. It is highly recommended to build KenLM with position-independent code (-fPIC) enabled, to enable python compatibility. After installing, run export KENLM_ROOT_DIR=... so that wav2letter++ can find it. This is needed because KenLM doesn't support a make install step.wav2letter++ expects audio and transcription data to be prepared in a specific format so that they can be read from the pipelines. Each dataset (test/valid/train) needs to be in a separate file with one sample per line. ...
    Downloads: 0 This Week
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  • 7
    Data Science at the Command Line

    Data Science at the Command Line

    Data science at the command line

    Command Line by Jeroen Janssens, published by O’Reilly Media in October 2021. Obtain, scrub, explore, and model data with Unix Power Tools. This repository contains the full text, data, and scripts used in the second edition of the book Data Science at the Command Line by Jeroen Janssens. This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You’ll learn how to combine small yet powerful...
    Downloads: 1 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
    fPotencia

    fPotencia

    Power flow library in C++

    ...Since Power system simulations have started needing to be executed in parallel, the old C-like designs are outdated; modular design is now needed to launch many simulations at the same time based on a base circuit. fPotencia is programmed in C++, but my intention is to bring JAVA, C#, Python and perhaps MATLAB versions of it. All of them in native code and whenever possible with the same modular structure.
    Downloads: 0 This Week
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  • 10
    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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