Hosted Jupyter
Hosted Jupyter is an accessible and powerful computing platform that provides a web-based interface for data analysis, interactive development and collaboration with open-source programming languages such as Python, R, Julia, and Scala.
Designed as an open-source platform, hosted Jupyter is supported by a large and active community of data scientists, technicians, and developers. It allows users to quickly create and share codes, documents, data analytics, and web-based visualizations from multiple sources. Users can conveniently launch Jupyter on remote machines and public clouds such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).
Hosted Jupyter offers many advantages for data scientists and developers including the ability to develop with popular programming languages, access over 150+ data science and machine learning libraries, and manage computation over remote machines. Furthermore, individual or team accounts may be created and managed in private, public or self-hosted environments. Hosted Jupyter also provides a comprehensive system architecture for securing your data with encryption and access policies.
In a nutshell, hosted Jupyter is an innovative and convenient platform for data analysis, cloud-based computing, and collaboration. It offers an array of tools, services, and features that support an expanding community of data scientists seeking to gain insight from their data and optimize their code execution.
