Wrangling Multimodal Data for Data Science Scenarios with big data technologies

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3412 Hillview Ave

3412 Hillview Ave · Palo Alto, CA

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Parking instructions: https://goo.gl/maps/efmhiJLAAkGNgvFH9 Special Instruction: Please, check in at reception

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Details

We invite you to join the Women in Big Data organization for the upcoming training at SAP.

In the age of Big Data, data enthusiasts struggle to bring various types of data such as graph, text, image, streaming, and relational together and run machine learning algorithms across them. Data scientists are looking for a language-agnostic platform which allows them to experiment and deploy without extra effort on-prem, in the cloud or both. The bigger problem is how to elastically extend or reduce the computation and storage power as needed without sabotaging the work done and Kubernetes technology is what makes the above features possible.
Our goal is to share our industry experience on how to address some of these obstacles and have some hands-on exercises on the Kubernetes technology and introduce you to the SAP big data solution for Data Scientists: SAP Data Intelligence.
Training will be hosted by Puntis Palazzolo (https://www.linkedin.com/in/puntis-palazzolo/).
Puntis is a Sr. Data Scientist at SAP where she manages the SAP Big Data solution, Developer-focused and Machine Learning and Artificial Intelligence topics in her role in SAP Data Hub/SAP Data Intelligence Product Management team. She has more than a decade of experience in software design and development, machine learning systems and database technologies in different industries such as Bioinformatics, Military and Health Care and applications such as Handwriting and Voice Recognition, Image Processing, Natural Language Processing and Recommendation Engines.
Puntis has several research publications in the field of Machine Learning and Data Science and has patented ideas in the field of Recommendation Engines.
Her academic background is in Computer and Electrical Engineering, Computer Science and Software Engineering.

Agenda:
9:30 AM-10AM Coffee & Networking
10-3 Training (lunch will be provided at noon)

Preparation: No prerequisite. This is a hands-on training, bring your laptop and have Google Chrome.