- Why is it Unique?
- BHC3 Integrated
- Data Integration
- AI/ML Development
- Operations and Security
- Deployment Options
Build, deploy, and operate Enterprise AI applications.
Third Party Support / Integrations
On-demand Jupyter Service
Use on-demand Jupyter environments running in configurable containers with open-source libraries from Conda, PIP, or CRAN
- Use Jupyter Notebook to view data stored in BHC3 Models
- Easily fetch instances of a BHC3 Model, and view as tables in a notebook
- Readily visualize and plot time series data
- Use your favorite libraries to visualize and explore data
Develop and run custom Python functions that are checked into your GitHub repository, tested using PyTest and CI/CD processes, then executed natively in a notebook or converted to an application API. Bring your own client in situations with remote connectivity and connect to all the BHC3 AI Suite data and services using Python and R SDKs.
Spend more time building better models when using state-of-the-art AI/ML technologies like Spark MLlib, TensorFlow, scikit-learn, cuDNN, SciPy, Caffe, PyTorch, AWS ML, Lex, Polly, Rekognition, Azure ML, H20.ai, Stanford Core NLP, and NLTK in one collaborative data science workspace built for the enterprise.