Real Time Vectorized DataSets under 30 minutes
10-07, 14:30–15:05 (Europe/London), Fañabe (Room 0.5)
Language: English

In our roles as Data Scientists or Data Engineers, we are delivering complex solutions for searching, recommendation engines or data extraction pipelines over complex data sets that expands the traditional data formats, as we incorporate all sorts of information generated by our clients and businesses.

This is a Show and Tell session where you would learn how to construct an AI powered database with real time ingestion capabilities under 30 minutes using Python and your own or public AI models.

The session will use Shapelets REC software stack and public AI models hosted in HuggingFace to create a real time repository of complex data (images, recordings, text, etc...) and an example of an application querying the repository with millisecond response times.


Data Engineering

Proposal Level

Intermediate (it is necessary to understand the related bases to go into detail)

Justo is founding member of Shapelets, where he helps the engineering team coding in Python and C++. Prior to Shapelets, Justo has had many senior appointments in the industry for the last 20 years, particularly around the telecoms, logistics and financial sectors.