Going From Unstructured Data to Vector Similarity Search

Abstract: 

One of the key concepts used in AI modeling is the storage and queqy of vectors. This workshop will start with 2 examples of unstructured data, images and journal abstracts. Participants will then work this data all the way through to a usable data store with an application on top it.

We will cover things such as transformers, embeddings, HuggingFace, choosing a vectorization model, and effective query composition. The python code needed to do this is quite easy to understand. If you want to work on your own laptop, there will be prerequisites published before hand. If not we will use a cloud hosted environment for you to do all your work. After this workshop you should be able to understand some of the concepts being used in these new AI architectures and have a better grasp on the work involved with building “AI” applications.

Bio: 

Steve is a dad, partner, son, and founder of Tech Raven Consulting. He can teach you about Data Analysis, Java, Python, PostgreSQL, Microservices, Containers, Kubernetes, and some JavaScript. He has deep subject area expertise in GIS/Spatial, Statistics, and Ecology. Before founding his company, Steve was a developer Advocate for VMware, Crunchy Data, DigitalGlobe, Red Hat, LinkedIn, deCarta, and ESRI. Steve has a Ph.D. in Ecology and can easily be bribed with offers of bird watching or fly fishing.

Open Data Science

 

 

 

Open Data Science
One Broadway
Cambridge, MA 02142
info@odsc.com

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