We have developed streamlined environments for production deployment to ensure performant models with the tools data scientists use most. Users and IT teams can configure and customize these environments to meet their specific needs.
R 3+, Python 2 and 3, Julia, Octave — all properly compiled and linked against high-performance BLAS libraries. Anaconda Python available upon request.
Jupyter, RStudio, Zeppelin, Beaker and more. Popular packages in R and Python, including pandas, scikit-learn, nltk, dplyr, caret, H2O, and hundreds more.
Including ggplot, matplotlib, bokeh, plotly, seaborn and more.
Properly configured to leverage GPUs: TensorFlow, Theano, Keras, and more.
Access Spark clusters from your code without painful configuration.
For Postgres, Oracle, MySQL and other popular databases.