Showing 9 open source projects for "qgis-osgeo4w-2.6.1-1-setup"

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    Build Securely on Azure with Proven Frameworks

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  • 1
    Nuclio

    Nuclio

    High-Performance Serverless event and data processing platform

    Nuclio is an open source and managed serverless platform used to minimize development and maintenance overhead and automate the deployment of data-science-based applications. Real-time performance running up to 400,000 function invocations per second. Portable across low laptops, edge, on-prem and multi-cloud deployments. The first serverless platform supporting GPUs for optimized utilization and sharing. Automated deployment to production in a few clicks from Jupyter notebook. Deploy one...
    Downloads: 13 This Week
    Last Update:
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  • 2
    marimo

    marimo

    A reactive notebook for Python

    marimo is an open-source reactive notebook for Python, reproducible, git-friendly, executable as a script, and shareable as an app. marimo notebooks are reproducible, extremely interactive, designed for collaboration (git-friendly!), deployable as scripts or apps, and fit for modern Pythonista. Run one cell and marimo reacts by automatically running affected cells, eliminating the error-prone chore of managing the notebook state. marimo's reactive UI elements, like data frame GUIs and plots...
    Downloads: 2 This Week
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  • 3
    PySyft

    PySyft

    Data science on data without acquiring a copy

    ... first putting it all in one (central) place. The Syft ecosystem seeks to change this system, allowing you to write software which can compute over information you do not own on machines you do not have (total) control over. This not only includes servers in the cloud, but also personal desktops, laptops, mobile phones, websites, and edge devices. Wherever your data wants to live in your ownership, the Syft ecosystem exists to help keep it there while allowing it to be used privately.
    Downloads: 1 This Week
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  • 4
    DearPyGui

    DearPyGui

    Graphical User Interface Toolkit for Python with minimal dependencies

    Dear PyGui is an easy-to-use, dynamic, GPU-Accelerated, cross-platform graphical user interface toolkit(GUI) for Python. It is “built with” Dear ImGui. Features include traditional GUI elements such as buttons, radio buttons, menus, and various methods to create a functional layout. Additionally, DPG has an incredible assortment of dynamic plots, tables, drawings, debuggers, and multiple resource viewers. DPG is well suited for creating simple user interfaces as well as developing complex...
    Downloads: 1 This Week
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  • Turn Your Content into Interactive Magic - For Free Icon
    Turn Your Content into Interactive Magic - For Free

    From Canva to Slides, Desmos to YouTube, Lumio works with the tech tools you are already using.

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  • 5
    NannyML

    NannyML

    Detecting silent model failure. NannyML estimates performance

    NannyML is an open-source python library that allows you to estimate post-deployment model performance (without access to targets), detect data drift, and intelligently link data drift alerts back to changes in model performance. Built for data scientists, NannyML has an easy-to-use interface, and interactive visualizations, is completely model-agnostic, and currently supports all tabular classification use cases. NannyML closes the loop with performance monitoring and post deployment data...
    Downloads: 0 This Week
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  • 6
    FlexiList.

    FlexiList.

    FlexiList is a Java data structure that combines the benefits of array

    FlexiList is a Java data structure that combines the benefits of arrays and linked lists. Like an array, it allows for efficient access to elements by index. Like a linked list, it allows for efficient insertion and deletion of elements at any position in the list. Benefits Over Arrays and ArrayList ->Efficient Insertion and Deletion: FlexiList can insert or delete nodes at any position in the list in O(1) time, whereas arrays require shifting all elements after the insertion or deletion...
    Downloads: 0 This Week
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  • 7
    ML workspace

    ML workspace

    All-in-one web-based IDE specialized for machine learning

    All-in-one web-based development environment for machine learning. The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on your own machines. This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard) perfectly...
    Downloads: 0 This Week
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  • 8
    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
    Last Update:
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  • 9
    DeepLearningProject

    DeepLearningProject

    An in-depth machine learning tutorial

    This tutorial tries to do what most Most Machine Learning tutorials available online do not. It is not a 30 minute tutorial that teaches you how to "Train your own neural network" or "Learn deep learning in under 30 minutes". It's a full pipeline which you would need to do if you actually work with machine learning - introducing you to all the parts, and all the implementation decisions and details that need to be made. The dataset is not one of the standard sets like MNIST or CIFAR, you...
    Downloads: 0 This Week
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  • Build Securely on AWS with Proven Frameworks Icon
    Build Securely on AWS with Proven Frameworks

    Lay a foundation for success with Tested Reference Architectures developed by Fortinet’s experts. Learn more in this white paper.

    Moving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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