Organizations use their data to make better decisions and build innovative experiences for their customers. With the exponential growth in data, and the rapid pace of innovation in machine learning (ML), there is a growing need to build modern data applications that are agile and scalable. In this episode, Jillian is joined by Vara Bonthu, Principal Solution ... Show More
Jul 7
#728: The Duck Talks Back - Using GENAI in Your Work
Simon shares some tips, tricks, and experiences in how Builders can use GENAI in their work to get things done faster, and with better outcomes. Links: Amazon Q Developer CLI: https://github.com/aws/amazon-q-developer-cli Promptz: https://www.promptz.dev/ AWS MCP Servers: https:/ ... Show More
23m 15s
Jun 23
#726: Single region, zero excuses: Mastering AWS resilience
Dive into single-region resilience with AWS experts John Formento and Tarik Makota as they debunk common misconceptions and share practical strategies for building robust applications. Learn why multi-AZ isn't enough on its own, discover key AWS services for resilience, and get a ... Show More
45m 33s
Jun 2021
Accelerating ML Training And Delivery With In-Database Machine Learning
Summary
When you build a machine learning model, the first step is always to load your data. Typically this means downloading files from object storage, or querying a database. To speed up the process, why not build the model inside the database so that you don’t have to move the ... Show More
1h 5m
Aug 2022
An Exploration Of The Expectations, Ecosystem, and Realities Of Real-Time Data Applications
Summary
Data has permeated every aspect of our lives and the products that we interact with. As a result, end users and customers have come to expect interactions and updates with services and analytics to be fast and up to date. In this episode Shruti Bhat gives her view on the ... Show More
1h 6m
Mar 2022
Bayesian Machine Learning with Ravin Kumar (Ep. 191)
This is one episode where passion for math, statistics and computers are merged. I have a very interesting conversation with Ravin, data scientist at Google where he uses data to inform decisions.
He has previously worked at Sweetgreen, designing systems that would benefit team ... Show More
31m 12s
Sep 2021
Declarative Machine Learning Without The Operational Overhead Using Continual
Summary
Building, scaling, and maintaining the operational components of a machine learning workflow are all hard problems. Add the work of creating the model itself, and it’s not surprising that a majority of companies that could greatly benefit from machine learning have yet to ... Show More
1h 11m