Showing 4 open source projects for "book making"

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  • Train ML Models With SQL You Already Know Icon
    Train ML Models With SQL You Already Know

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    $300 Free Credits to Build on Google Cloud

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    ADAMANT Market-Making Software

    ADAMANT Market-Making Software

    Free self-hosted liquidity bot for token issuers

    Maintain order book depth, tighter spreads, price ranges, and live-like market activity on supported CEXs — without sending your tokens, funds, or API keys to a third-party market maker.
    Downloads: 123 This Week
    Last Update:
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  • 2
    Cal.com

    Cal.com

    Scheduling infrastructure for absolutely everyone

    Meet Cal.com, the event-juggling scheduler for everyone. Focus on meetings, not making meetings. Free for individuals. Cal reads your availability from all your existing calendars ensuring you never get double booked! Set repeating schedules for the times of the day and week that you want people to be able to book you. Share your short cal.com personal link and make it incredibly easy for people to book a meeting at a time that works for both of you!
    Downloads: 10 This Week
    Last Update:
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  • 3
    EasyAppointments

    EasyAppointments

    Easy!Appointments - Self Hosted Appointment Scheduler

    ...Appointments is an open-source appointment management system that helps businesses schedule and manage client appointments efficiently. It offers a web-based interface where clients can book appointments online, while administrators can manage staff schedules, services, and customer data. The system is highly customizable and can be integrated with other tools like Google Calendar, making it ideal for small businesses, clinics, and service providers.
    Downloads: 4 This Week
    Last Update:
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  • 4
    Bayesian Julia

    Bayesian Julia

    Bayesian Statistics using Julia and Turing

    Bayesian statistics is an approach to inferential statistics based on Bayes' theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used for making predictions about future events. Bayesian statistics is a departure from...
    Downloads: 5 This Week
    Last Update:
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    99.99% Uptime for MySQL and PostgreSQL Databases

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