Showing 2 open source projects for "python framework"

View related business solutions
  • Multi-Entity Cloud Accounting Software for Growing Businesses Icon
    Multi-Entity Cloud Accounting Software for Growing Businesses

    Built for small to midsize businesses that have outgrown entry-level accounting or legacy ERP solutions.

    Built natively on the Microsoft Power Platform (Dynamics 365), Gravity delivers robust multi-entity financial management with seamless integration to Microsoft 365, Power BI, Teams + Copilot — no third-party add-ons required.
    Learn More
  • Time tracking software for the global workforce Icon
    Time tracking software for the global workforce

    Teams of all sizes and in various industries that want the best time tracking and employee monitoring solution.

    It's easy with Hubstaff, a time-tracking and workforce management platform that automates almost every aspect of running or growing a business. Teams can track time to projects and to-dos using Hubstaff's desktop, web, or mobile applications. You'll be able to see how much time your team spends on different tasks, plus productivity metrics like activity rates and app usage through Hubstaff's online dashboard. Most of the available features are customizable on a per-user basis, so you can create the team management tool you need.
    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