Use on-demand Jupyter environments running in configurable containers with open-source libraries from Conda, PIP, or CRAN
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 C3 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.
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