Austin Data Geeks

This is a partner event. To attend, register at: https://go.scylladb.com/wbn-scylla-dynamodb-kubernetes-registration.html Henrik Johansson and Tzach of ScyllaDB will demonstrate Alternator, Scylla's new DynamoDB-compatible API, which allows you to take your locked-in DynamoDB workloads and run them anywhere: on-premises, on other public clouds like Microsoft Azure or Google Cloud Platform, still on AWS (such as the high-density i3en instances) or as a fully managed DBaaS. Alternator allows you to take advantage of Scylla, a cost effective drop-in open source alternative to DynamoDB. The session will cover: Scylla Alternator: Scylla’s Amazon DynamoDB-compatible API Scylla Operator: Running Scylla Alternator on Kubernetes Demo Alternator - Demo and explain DynamoDB on GKE Speaker bios: Henrik Johansson, Software Engineer, ScyllaDB Henrik is a software engineer working on Scylla management. He’s a Go enthusiast and long time Linux user. He has a background in Physics but has worked professionally as an engineer with backend development for the past 18 years. Tzach Livyatan, VP of Product, ScyllaDB Tzach Livyatan has a B.A. and MSc in Computer Science (Technion, Summa Cum Laude), and has had a 15 year career in development, system engineering and product management. In the past he worked in the Telecom domain, focusing on carrier grade systems, signalling, policy and charging applications. To attend, register at: https://go.scylladb.com/wbn-scylla-dynamodb-kubernetes-registration.html

This is a partner event with our friends at the Bay Area NLP Meetup For a link to the event: RSVP at https://www.meetup.com/Bay-Area-NLP/events/271843560/ Summary: How do you train a model on small amounts of data on complex tasks such as question answering or medical relation extraction? One area of research that tackles this is transfer learning, which focuses on training models to learn knowledge and skills from other related tasks that will transfer and boost performance on tasks of interest. However, what does transfer learning look like in practice? This talk will go over practical tips and tricks for setting up transfer learning experiments, as well as hard-learned lessons of understanding which tasks will transfer well to others. Bio: Yada Pruksachatkun (https://www.yadapruk.com/) is an incoming Applied Scientist at Amazon Alexa working on fairness and bias in NLU. She recently completed graduate school at NYU, where her research on transfer learning was recently presented at 2020 ACL (https://arxiv.org/abs/2005.00628). Aside from machine learning, she has a deep interest in healthcare, and has worked on a variety of projects using machine learning in healthcare. Online Event: For a link to the event: RSVP at https://www.meetup.com/Bay-Area-NLP/events/271843560/

Angel / Supporter tickets now available at: https://data-day-texas-2021.eventbrite.com 11 years of Data Day Texas! Originally launched in January 2011, Data Day Texas is the longest running NoSQL / BigData conference in the world. Each year, Data Day Texas highlights the latest tools, techniques, and projects in the data / ai space, bringing speakers and attendees from around the world to enjoy the hospitality that is uniquely Austin. To preserve the spirit of the event, we cap registration at 1000 attendees. Our 2021 edition will feature tracks on Data Engineering, Data Science, Machine Learning, Natural Language Processing, Human in the Loop, Graph Databases and processing, and more. 2021 website coming soon.