Showing 7 open source projects for "work time"

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  • 1
    GenAI Processors

    GenAI Processors

    GenAI Processors is a lightweight Python library

    GenAI Processors is a lightweight Python library for building modular, asynchronous, and composable AI pipelines around Gemini. Its central abstraction is the Processor, a unit of work that consumes an asynchronous stream of parts (text, images, audio, JSON) and produces another stream, making it natural to chain operations and keep everything streaming end-to-end. Processors can be composed sequentially (to build multi-step flows) or in parallel (to fan-out work and merge results), which makes sophisticated agent behaviors easy to express with simple operators. ...
    Downloads: 1 This Week
    Last Update:
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  • 2
    SENAITE LIMS

    SENAITE LIMS

    SENAITE Meta Package

    ...SENAITE can be easily integrated with instruments by using off-the-shell interfaces for data import and export. Custom interfacing is supported too. Import instrument results and avoid human errors in the carrying-over process. Reduce the turnaround time on results report delivery. Assign priorities to samples and due dates for tests, plan and assign the daily work by using worksheets, and keep track of delayed tests immediately.
    Downloads: 7 This Week
    Last Update:
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  • 3
    Lightweight' GAN

    Lightweight' GAN

    Implementation of 'lightweight' GAN, proposed in ICLR 2021

    ...Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before they pass into a neural network (if you use augmentation). The general recommendation is to use suitable augs for your data and as many as possible, then after some time of training disable the most destructive (for image) augs. You can turn on automatic mixed precision with one flag --amp. ...
    Downloads: 3 This Week
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  • 4
    Homemade Machine Learning

    Homemade Machine Learning

    Python examples of popular machine learning algorithms

    ...Each algorithm is accompanied by mathematical explanations, visualizations (often via Jupyter notebooks), and interactive demos so you can tweak parameters, data, and observe outcomes in real time. The purpose is pedagogical: you’ll see linear regression, logistic regression, k-means clustering, neural nets, decision trees, etc., built in Python using fundamentals like NumPy and Matplotlib, not hidden behind API calls. It is well suited for learners who want to move beyond library usage to understand how algorithms operate internally—how cost functions, gradients, updates and predictions work.
    Downloads: 0 This Week
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  • 5
    eCxx

    eCxx

    A C++ library for AVR and NodeMCU

    NOTE: This project is marked with 'Status: Abandoned' on SourceForge because not enough time can be dedicated to this project. However it may still get sporadic commits to the repository. eCxx is a library for AVR and NodeMCU tailored for micro LED displays and lighting effects. eCxx is utilizing Makefile build system. Java and Python based applications/tools are also included to ease the development and debugging process using the host PC.
    Downloads: 0 This Week
    Last Update:
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  • 6
    Django REST Pandas

    Django REST Pandas

    Serves up Pandas dataframes via the Django REST Framework

    ...While DRP is primarily a data API, it also provides a default collection of interactive visualizations through the @wq/chart library, and a @wq/pandas loader to facilitate custom JavaScript charts that work well with CSV output served by DRP. These can be used to create interactive time series, scatter, and box plot charts.
    Downloads: 0 This Week
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  • 7
    ...The purpose of this project is to make a python WebDAV client library that is easy and convenient to use, while remaining flexible enough for developers who may want a finer grain of control. UPDATE: The test suite passes using Python 3.1 so we will now be supporting Python3 issues. The library will try to continue to work on both Python 2 and Python 3 until such a time that we find something that is not backwards compatible between the Python releases.
    Downloads: 0 This Week
    Last Update:
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