Oracle Data Science Cloud

About

Oracle Data Science Cloud is a collaborative platform for data scientists to build and manage ML models. Leveraging open source technology, it provides a scalable cloud-based platform for data scientists to explore data and train, save, and deploy models, while utilizing the rich Python ecosystem as well as Oracle's proprietary Python libraries. • Data Analysts - Oracle Analytics Cloud delivers cutting-edge visualization, augmented analysis, and natural language processing through an easy-to-use interface. Powered by AI and machine learning, Oracle Analytics Cloud makes it possible for any level of user to generate deep insights and create forward-thinking reports. • Data Engineers - Oracle Database's Machine Learning capabilities bring the latest automation and self-learning tools to the database space. The result is an experience that's both powerful and user-friendly. Using Oracle's tools, it's easier than ever to manage data and support application development on a secure and scalable infrastructure.

The platform combines three key components: • Infrastructure - systems tasks (like spawning servers) are abstracted and handled automatically so data scientists can focus on the substance of their work. • Tools - open source tools (like Jupyter, R Shiny, or modeling libraries) that data scientists need are integrated into a centralized place. • Workflow - automation for tasks, collaboration, and communication that let data science teams effectively deliver on their mission.

**The presentation is going to include a live showcase of the Oracle Data Science Cloud platform using a simple user scenario!**

Oracle Cloud Infrastructure offers exceptional performance, security, and control for today's most demanding high-performance computing (HPC) research workloads. The Oracle HPC cloud consists of: • Bare metal instances support applications requiring high core counts, large amounts of memory, and high memory bandwidth. Users can build cloud environments with…