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    MongoDB Atlas runs apps anywhere

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    MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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    Gemini 3 and 200+ AI Models on One Platform

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    Build generative AI apps with Vertex AI. Switch between models without switching platforms.
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  • 1
    Alibi Explain

    Alibi Explain

    Algorithms for explaining machine learning models

    Alibi is a Python library aimed at machine learning model inspection and interpretation. The focus of the library is to provide high-quality implementations of black-box, white-box, local and global explanation methods for classification and regression models.
    Downloads: 8 This Week
    Last Update:
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    EvoTorch

    EvoTorch

    Advanced evolutionary computation library built on top of PyTorch

    EvoTorch is an evolutionary optimization framework built on top of PyTorch, developed by NNAISENSE. It is designed for large-scale optimization problems, particularly those that require evolutionary algorithms rather than gradient-based methods.
    Downloads: 0 This Week
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  • 3
    Deep Reinforcement Learning for Keras

    Deep Reinforcement Learning for Keras

    Deep Reinforcement Learning for Keras.

    keras-rl implements some state-of-the-art deep reinforcement learning algorithms in Python and seamlessly integrates with the deep learning library Keras. Furthermore, keras-rl works with OpenAI Gym out of the box. This means that evaluating and playing around with different algorithms is easy. Of course, you can extend keras-rl according to your own needs. You can use built-in Keras callbacks and metrics or define your own. Even more so, it is easy to implement your own environments and even algorithms by simply extending some simple abstract classes. ...
    Downloads: 7 This Week
    Last Update:
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  • 4
    General purpose agents using reinforcement learning. Combines radial basis functions, temporal difference learning, planning, uncertainty estimations, and curiosity. Intended to be an out-of-the-box solution for roboticists and game developers.
    Downloads: 0 This Week
    Last Update:
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