Deephaven Community Core's documentation includes several simple how-tos and a section of comprehensive reference articles to get you started.
This month, we published a tutorial to familiarize new users with Deephaven's primary features. Follow along to learn how to get your data into Deephaven and basic querying techniques.
We also added new docs teaching users how to:
- use PyTorch, SciKit, and Tensorflow in Deephaven, which help to get you started building machine learning models.
- use Pandas and Numba in Python queries.
- navigate the user interface, such as the Chart Builder feature, which easily creates data visualizations.
- calculate EMAs, one of our built-in methods.
Our blog continues to grow with examples of using Deephaven for topical use cases, such as cryptocurrency trading.