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AWS re: Invent 2021 Artificial Intelligence and Machine Learning Session Guide for Builders and Architects
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AWS re: Invent 2021 Artificial Intelligence and Machine Learning Session Guide for Builders and Architects

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November 10, 2021
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Last Updated on July 26, 2023 by Editorial Team

Author(s): Juv Chan

Originally published on Towards AI.

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My Top 5 Recommendations

Welcome to AWS re:Invent at The Venetian Las Vegas in 2019. © Juv Chan. All rights reserved.

Preface

I create this guide to share my top 5 most looking forward to sessions for AWS re: Invent 2021 attendees who are interested in the Artificial Intelligence and Machine Learning (AI & ML) sessions. There are more than 100 AI & ML track sessions this year.

If you have yet to register for AWS re:Invent 2021 which will begin on Nov. 29 until Dec. 3, you can still register at their registration page. Full session details are available in the re: Invent sessions dashboard after you have completed registration and logged on.

Note that virtual attendees can live stream keynotes and leadership sessions, and breakout sessions will be available on-demand after the event.

Top 5 Sessions for AI & ML Builders & Architects

1. KYN003: Swami Sivasubramanian Keynote

Wed., Dec. 1 8:30 AM — 10:30 AM PST U+007C In-Person & Virtual

Listen to Dr. Swami Sivasubramanian, Vice President, Amazon Machine earning, and other speakers on the latest key development and innovations in AWS AI & ML. There are new product & service launches, customer stories, demos, and more in this 2-hour Machine Learning keynote session.

If you’re interested to find out more on the past re: Invent Machine Learning keynote, the full video session and blogs are available below.

2. AIM416: Using Hugging Face models on Amazon SageMaker (Workshop)

Mon., Nov. 29, 4:45 PM — 7:00 PM PST U+007C In-Person U+007C Session Calendar Invite

Hugging Face is a fast-growing, popular, open-source AI/ML community hub for Natural Language Processing (NLP) models, datasets, as well as community ML apps, demo spaces.

I am very keen to learn how I can quickly train a Hugging Face transformer NLP model on Amazon SageMaker with just a few lines of code using PyTorch or TensorFlow with SageMaker’s distributed training libraries in this workshop. I strongly recommend this workshop session to builders who are interested in building NLP apps with Hugging Face and SageMaker.

3. ARC323: Designing Well-Architected machine learning workloads (Chalk Talk)

Wed., Dec. 1 3:15 PM — 4:15 PM PST U+007C In-Person

You will learn about the Machine Learning Lens for the AWS Well-Architected Framework which provides you with a set of established best practices and architectural principles for designing workloads across ML lifecycle phases. This session is recommended for architects or builders who are interested in designing and applying architectural best practices to their ML workloads.

4. AIM417: Easily deploy models for the best performance & cost using Amazon SageMaker (Breakout Session)

Wed., Dec. 1, 5:30 PM — 6:30 PM PST U+007C In-Person & Virtual (On-Demand)U+007C Session Calendar Invite

Performance efficiency and cost optimization are two of the five pillars in the AWS Well-Architected Framework which represent the abilities to use computing resources efficiently to meet system requirements and deliver business value at the lowest price point.

This session is recommended for builders who want to learn how to use Amazon SageMaker to run performance benchmarks and load tests for inference to determine the right instance types sizing and model optimizations for the best cost-performance efficiency.

5. AMZ302: MLOps at Amazon: How to productionize ML workloads at scale (Breakout Session)

Thur., Dec. 2, 2:30 PM — 3:30 PM PST U+007C In-Person & Virtual (On-Demand)

MLOps (Machine Learning Operations) accelerates the delivery of ML production workloads continuously and automatically. More organizations are using or going to use MLOps to optimize the production lead time and other operational metrics of their ML workload.

Discover from this session how AWS MLOps can help to reduce production-level ML infrastructure delivery time from weeks to hours (with specific data and examples from Amazon) and allow reusability or generation of new ML solutions easily.

Special Mention: First annual AWS BugBust re: Invent Challenge

Nov. 29 10:00 AM — Dec. 3 2:00 PM PST U+007C In-Person & Virtual

The AWS BugBust re:Invent Challenge is open to all developers who have Python or Java knowledge regardless of whether or not they’re attending re:Invent. There will be an array of prizes, from hoodies and fly swatters to Amazon Echo Dots, available to all who participate and meet certain milestones in the challenge.

There’s also the coveted title of “Ultimate AWS BugBuster” accompanied by a cash prize of $1500 for whomever earns the most points by squashing bugs during the event.

To register or learn more about this challenge, the relevant links are as below.

AWS BugBust

AWS BugBust

AWS BugBust bugbust.aws

Help Make BugBusting History at AWS re:Invent 2021 U+007C Amazon Web Services

Earlier this year, we launched the AWS BugBust Challenge, the world's first global competition to fix one million code…

aws.amazon.com

AWS BugBust Challenges Developers to Set World Record for Bug Busting at re:Invent 2021

Software bugs are irksome, time-consuming and can be one of the most expensive software development costs for any…

devops.com

Have fun and enjoy your re:Invent sessions and experience! Feel free to share your thoughts or questions on this post.

Hilarious T-Rex costumes at AWS re:Invent 2019. © Juv Chan. All rights reserved.
Hilarious Hippo costumes at AWS re:Invent 2019. © Juv Chan. All rights reserved.

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//Articles to skip let articleIdsToSkip = ['post-2651', 'post-3414', 'post-3540']; //keyword with its related achortag is recieved here along with article id function searchAndReplace(keyword, anchorTag, articleId) { //selects the h3 h4 and p tags that are inside of the article let content = document.querySelector(`#${articleId} .entry-content`); //replaces the "linktext" in achor tag with the keyword that will be searched and replaced let newLink = anchorTag.replace('linktext', keyword); //regular expression to search keyword var re = new RegExp('(' + keyword + ')', 'g'); //this replaces the keywords in h3 h4 and p tags content with achor tag content.innerHTML = content.innerHTML.replace(re, newLink); } function articleFilter(keyword, anchorTag) { //gets all the articles var articles = document.querySelectorAll('article'); //if its zero or less then there are no articles if (articles.length > 0) { for (let x = 0; x < articles.length; x++) { //articles to skip is an array in which there are ids of articles which should not get effected //if the current article's id is also in that array then do not call search and replace with its data if (!articleIdsToSkip.includes(articles[x].id)) { //search and replace is called on articles which should get effected searchAndReplace(keyword, anchorTag, articles[x].id, key); 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mlclinks = document.querySelectorAll(`#${c.id} .entry-content a.mlc-link`); llinks = document.querySelectorAll(`#${c.id} .entry-content a.l-link`); pbplinks = document.querySelectorAll(`#${c.id} .entry-content a.pbp-link`); //sending the anchor tags list of each article one by one to remove extra anchor tags removeLinks(dslinks); removeLinks(mllinks); removeLinks(ailinks); removeLinks(nllinks); removeLinks(deslinks); removeLinks(tdlinks); removeLinks(iaslinks); removeLinks(mlclinks); removeLinks(llinks); removeLinks(pbplinks); } }); } //To remove extra achor tags of each category (ds, ml, ai) and only have 2 of each category per article cleanLinks(); */ //Recommended Articles var ctaLinks = [ /* ' ' + '

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