Jupyter Pi Deprecated 20231120

Jupyter Pi

AI development platform for multi-user

Address the inconvenience of limited computing resources experienced by AI / Big Data professionals.
We provide the necessary development environment and tools in advance so that we can concentrate on AI research.
Research, execute, and share AI algorithms through the Web.

Multi-user data, share research

Elastic AI
Infrastructure

Secure elastic AI infrastructure technology

Applied to various infrastructure environments

On-Prem,Workstation,Cloud

Web-based integrated development environment

Easy AI work environment

configuration

Fully configured in just seconds

Secure AI Learning Environment

Deploy on

any infrastructure

Cloud environment, workstation environment, etc.

Configuration through various infrastructures

Improved

interoperability

Improved work efficiency through research

collaboration between team members

Resource management

The service manager can check the usage and status of the entire infrastructure in real time.

Efficient Resource Utilization

Dynamic scheduling

Provides dynamic support management and scheduling to increase expensive equipment utilization.

live monitoring

Team and organizational units can see user and resource utilization and current user information in real time.

Development environment regardless of place

The development environment is provided immediately on the web without the need of installing various libraries for development. No matter where you are, you can continue with version control and development on any device.

Development environment setting with one click

Data science, machine learning, financial analysis, time series data analysis and web service development can be used for various situations and purposes.

It includes open source such as Pandas, Keras and Django, and you can add new libraries at any time.

Share your work progress

Share notebooks with team members and colleagues, including result reports and code. Access team-level dataset libraries and algorithms created by others.

Infrastructure auto installation

Can be installed in infrastructure of various sizes
Scalable Architecture Design

  • Multiuser Support and Management Tools
  • User-friendly interactive AI development environment
  • Various frameworks for AI learning
    Integrated integration through container technology
  • Dynamic resource management and scheduling to increase hourly utilization of expensive equipment
  • Can be deployed in a variety of environments, including workstations, servers, and cloud environments Provisioning technology