TensorFlow is also available for use in Cloud Datalab, a beta cloud service and Docker image that is based on Jupyter (formerly IPython) notebooks.

Among the Jupyter extensions is the ability to “decompose” different AI development tasks into different notebooks, allowing each to use different frameworks such as TensorFlow for deep learning ...

Recommendation: These example notebooks demonstrate how to use NVTabular with TensorFlow, PyTorch, and HugeCTR. Each example provides additional details about the end-to-end workflow, which ...

Jupyter Notebook combines live code, graphics, visualizations, and text in shareable notebooks that run in a web browser ...

Jupyter creates interactive documents to mix code, text, and graphics. Jupyter is popular for sharing code and results in scientific computing. Jupyter notebooks consist of Markdown and code cells ...

Jupyter notebooks break out of their "show and tell" role into something more suitable to data engineers. Can JupyterLab turn notebooks into an Enterprise tool?

Google Colab and Jupyter Notebook are powerful tools for coding and data analysis, each offering unique features and benefits. Compare them to choose the best fit for your needs.

JetBrains unveiled an on-premises edition of the Jupyter Notebook collaboration platform for building prototypes of AI models.

TOOLBOX 30 October 2018 Why Jupyter is data scientists’ computational notebook of choice An improved architecture and enthusiastic user base are driving uptake of the open-source web tool.