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Showing 2 open source projects for "keras"

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    Gen AI apps are built with MongoDB Atlas

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    Powerful Business Process Automation

    With ThinkAutomation, you get an open-ended studio to build any and every automated workflow you could ever need.

    When a message is received ThinkAutomation automatically executes one or more Automations. Automations are created using an easy to use drag-and-drop interface to run simple or complex tasks. Automations can perform many business process Actions, including: updating company databases, CRM systems and cloud services, sending outgoing emails, Teams & SMS messages, document processing, custom scripting, integration and much more. Over 100 built-in actions are included, plus ThinkAutomation is extensible with Custom Actions.  
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  • 1
    ktrain

    ktrain

    ktrain is a Python library that makes deep learning AI more accessible

    ktrain is a Python library that makes deep learning and AI more accessible and easier to apply. ktrain is a lightweight wrapper for the deep learning library TensorFlow Keras (and other libraries) to help build, train, and deploy neural networks and other machine learning models. Inspired by ML framework extensions like fastai and ludwig, ktrain is designed to make deep learning and AI more accessible and easier to apply for both newcomers and experienced practitioners. With only a few lines of code, ktrain allows you to easily and quickly. ktrain purposely pins to a lower version of transformers to include support for older versions of TensorFlow. ...
    Downloads: 6 This Week
    Last Update:
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  • 2
    Python Tutorials

    Python Tutorials

    Machine Learning Tutorials

    ...This includes foundational Python concepts, data processing with libraries like NumPy and pandas, threading and multiprocessing for concurrency, and practical use of libraries such as Matplotlib for data visualization. It also provides tutorials on machine learning frameworks and concepts, including TensorFlow, PyTorch, Keras, Scikit-Learn, and reinforcement learning techniques. Each section contains organized code and explanations designed to help learners understand the underlying mechanics of Python and common computational approaches.
    Downloads: 0 This Week
    Last Update:
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