Showing 2 open source projects for "framework python"

View related business solutions
  • All-in-One Mental Health EHR Icon
    All-in-One Mental Health EHR

    Simplify your systems. Strengthen your cash flow. Start fresh with Ensora Health

    Ensora Health’s Mental Health EHR is designed for mental health professionals, therapists, and practice managers looking for a secure, user-friendly solution to streamline administrative tasks and improve efficiency in their practice management
    Learn More
  • Windocks - Docker Oracle and SQL Server Containers Icon
    Windocks - Docker Oracle and SQL Server Containers

    Deliver faster. Provision data for AI/ML. Enhance data privacy. Improve quality.

    Windocks is a leader in cloud native database DevOps, recognized by Gartner as a Cool Vendor, and as an innovator by Bloor research in Test Data Management. Novartis, DriveTime, American Family Insurance, and other enterprises rely on Windocks for on-demand database environments for development, testing, and DevOps. Windocks software is easily downloaded for evaluation on standard Linux and Windows servers, for use on-premises or cloud, and for data delivery of SQL Server, Oracle, PostgreSQL, and MySQL to Docker containers or conventional database instances.
    Learn More
  • 1
    PyBroker

    PyBroker

    Algorithmic Trading in Python with Machine Learning

    Are you looking to enhance your trading strategies with the power of Python and machine learning? Then you need to check out PyBroker! This Python framework is designed for developing algorithmic trading strategies, with a focus on strategies that use machine learning. With PyBroker, you can easily create and fine-tune trading rules, build powerful models, and gain valuable insights into your strategy’s performance.
    Downloads: 2 This Week
    Last Update:
    See Project
  • 2
    AlphaPy

    AlphaPy

    Python AutoML for Trading Systems and Sports Betting

    AlphaPy is a Python-based AutoML framework tailored for trading systems and sports betting applications. Built on popular libraries like scikit-learn and pandas, it enables data scientists and speculators to craft predictive models, ensemble strategies, and automated forecasting systems with minimal setup. Run machine learning models using scikit-learn, Keras, xgboost, LightGBM, and CatBoost.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB