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After last year's amazing fully virtual event and improvement in the current life situation, Amazonians can finally gather back to Vegas for a somewhat traditional re:Invent. But this year will be the second year that re:Invent has a large virtual/remote part.
If you are like me you are not from the USA and cannot easily travel to Las Vegas. I have the perfect remote guide for your perfect virtual re:Invent 2021 focused on NLP and Machine Learning.
And then maybe next year we will see each other in Las Vegas. 🤞🏻
If you haven't yet registered for free do it now at https://reinvent.awsevents.com/register/
Guide
Let's start with the obvious ones. Key Note and Key Note. It will be the first year after Andy Jassy became Amazon CEO and is not doing the opening key anymore. This year it is Adam Selipsky turn.
I can really recommend both keynotes to everyone, whether machine learning-oriented or not. They give an update on all the new developments, services, solutions, achievements, and much more.
[ARS202] AWS re:Invent keynote live stream: CEO
Tuesday, November 30; 8:30 AM - 10:00 AM PDT; 5:30 PM - 7:00 PM CET;
Adam Selipsky, AWS CEO, takes the stage to share his insights and the latest news about AWS customers, products, and services.
[ARS203] AWS re:Invent keynote live stream: Machine learning
Wednesday, December 1; 8:30 AM - 10:00 AM PDT; 5:30 PM - 7:00 PM CET;
Join Swami Sivasubramanian, Vice President, Amazon Machine Learning, on an exploration of what it takes to put data in action with an end-to-end data strategy including the latest news on databases, analytics, and machine learning.
Now let's get into my top 5 remote available Sessions.
*Quick Note: Sadly workshops, builders' sessions, Chalk Talks will only be in-person unfortunately, and will not be recorded*
[AIM328] Automatically scale Amazon SageMaker endpoints for inference
Thursday, December 2; 3:15 PM - 4:15 PM; 12:15 AM - 1:15 AM CET;
Many customers organizations have ML applications with intermittent usage patterns. As a result, customers they end up provisioning for peak capacity up front, which results in idle capacity. In this session, learn how to use Amazon SageMaker to reduce costs for intermittent workloads and scale automatically based on your needs.
[STP219] DayTwo redefines microbiome analysis using AWS frameworks
Tuesday, November 30; 11:00 AM - 11:50 AM; 8:00 PM - 8:50 PM CET;
In this session, learn how DayTwo used AWS to create the world’s largest, highest-resolution microbiome genomic analysis pipeline. Discover how this enabled data scientists to mine 300 terabytes of genomic datasets, revealing completely new biomarkers and unknown links between the gut microbiome and human health. Then, find out how DayTwo used AWS genomic analysis Quick Starts to build a process workflow on the Nextflow open-source framework and how the company processed huge segments of data to reveal new insights. Finally, hear how DayTwo uses Amazon SageMaker to train predictive machine learning models for early detection of health conditions.
[LFS305] Delivering life-changing medicines at AstraZeneca with data and AI
Tuesday, November 30; 12:30 PM - 1:30 PM; 9:30 PM - 10:30 PM CET;
Join this session to learn how AstraZeneca is driving insights at scale and putting the power of artificial intelligence (AI) in the hands of employees by enabling self-service capabilities on AWS, helping them deliver life-changing medicines. Discover how AstraZeneca has implemented an AI-driven drug discovery platform to increase quality and reduce the time it takes to discover a potential drug candidate. Learn how AstraZeneca hosts predictive machine learning models, generative AI, a global analytical database, and molecule search capabilities, and how it uses services such as Amazon EKS, Amazon ES, Amazon Kinesis, Amazon Aurora PostgreSQL, and open-source tools to build and optimize its platform on AWS.
[AIM417] Easily deploy models for the best performance & cost using Amazon SageMaker
Wednesday, December 1; 5:30 PM - 6:30 PM; 2:30 AM - 3:30 AM CET;
Optimizing cloud resources to achieve the best cost and performance for your ML model is critical. In this session, learn how to use Amazon SageMaker to run performance benchmarks and load tests for inference to determine the right instance types and model optimizations.
[AIM320] Implementing MLOps practices with Amazon SageMaker, featuring Vanguard
Thursday, December 2; 2:30 PM - 3:30 PM; 11:30 PM - 12:30 AM CET;
Implementing MLOps practices helps data scientists and operations engineers collaborate to prepare, build, train, deploy, and manage models at scale. During this session, explore the breadth of MLOps features in Amazon SageMaker that help you provision consistent model development environments, automate ML workflows, implement CI/CD pipelines for ML, monitor models in production, and standardize model governance capabilities. Then, hear from Vanguard as they share their journey enabling MLOps to achieve ML at scale for their polyglot model development platforms using Amazon SageMaker features, including SageMaker projects, SageMaker Pipelines, SageMaker Model Registry, and SageMaker Model Monitor.
Bonus Tip:
[OPN320] Using Rust to minimize environmental impact
Monday, November 29; 11:30 AM - 12:30 PM; 8:30 PM - 9:30 AM CET;
Rust is one of the most energy-efficient and safe programming languages. With Rust, it may be possible to reduce the environmental impact of the IT industry by 50% and prevent 70% of all high-severity CVEs. In this session, dive into the "superpowers" of Rust, hear about the work ahead to give those powers to every engineer and hear the ways you can contribute.
Conclusions
I know being remote for an on-side conference is not easy but AWS is doing a great job to give us access to great sessions. It will be a great conference for all, continuously raising the bar in the cloud and machine learning domain.
Have fun and enjoy the conference. And never stop building great things!
Don't forget to sign up at https://reinvent.awsevents.com/register/
Thanks for reading. If you have any questions, feel free to contact me on Twitter or LinkedIn.