Deephaven is a full-stack live data framework that Wall Street analysts, machine learning engineers, data scientists, and many other professionals rely on for data analysis and transformation. Whether you’re creating Bollinger bands to analyze financial instruments, conducting research that requires transforming large amounts of data, or building a machine learning model, Deephaven can streamline and empower your workflow.
Deephaven is fast, efficient, versatile, and easy to use – and with the release of our new Crash Course and demo notebooks, it’s never been easier to learn than now.
Deephaven’s new Crash Course is available for both Python and Groovy users. It presents Deephaven’s key concepts and features in an intuitive, logical order, with clear and concise guides on all of Deephaven’s core functionalities:
And more!
Clear and concise documentation is important, but it’s no replacement for hands-on learning. The new Crash Course now appears in the Deephaven demo notebooks, where you can easily run code blocks and see the results in real time. Crash Course notebooks are available in both the Deephaven Code Studio and the JupyterLab interface, so you can learn in the environment that suits you best.
Our Community documentation has all the resources you need to become a Deephaven power user. Our Slack community continues to grow, and we’d love to have you join us! If you have any questions, comments, or suggestions, please reach out to us there.
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