Don’t miss episode 3 of the machine learning training series on Twitch

We are now two episodes into the seven-week AWS Power Hour: Machine Learning series. Are you caught up? If not, catch the recorded streams! And make sure you join us for Episode 3 this Thursday, August 6 at 4 p.m. PST on Twitch.

Episode 2 Recap

Kashif Imran, AWS Principle Solution Architect, joined hosts Jon Dion and Kirsten Dupart to help us understand how to get started with Amazon Textract. The chat was lively again (who *doesn’t* hate expense reports?!) and while we were sad to learn that Amazon Textract can’t handle extraterrestrial languages, we were pretty impressed with what it can do.

Coming in Episode 3

In episode 3, Jon and Kirsten will be joined by Mona Mona, AWS ML/AI Specialist Solutions Architect. We’ll help you build on what you learned last week about using ML to extract text and data from documents so you can start gaining greater insights from that text via Amazon Comprehend. You’ll get an overview of Amazon Comprehend, a natural language processing (NLP) service that uses ML to find insights and relationships in text, and spend some time in the AWS Management Console. You’ll see the service in action, with a focus on features like key phrase extraction, sentiment analysis, and entity recognition.

What is AWS Power Hour: Machine Learning?

AWS Power Hour: Machine Learning is a weekly, live-streamed program that premiered Thursday, July 23 at 4 p.m. PST and airs at that time every Thursday for seven weeks. Each show will feature the AWS hosts and a special guest as they demonstrate how to build apps with AI Services from AWS. Designed for developers without prior ML experience, the show will help you learn to build apps that showcase natural language, speech recognition, and other personalized recommendations. The show provides in-depth technical education in a fun and interactive environment.

Join us for the next episode on August 6

Join the live stream each week to submit questions and participate in weekly challenges, or watch the recorded episodes on Twitch whenever it’s convenient for you.