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

Author(s): Juv Chan

Originally published on Towards AI.

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My Top 5 Recommendations

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.

• AWS re:Invent 2020 — Machine Learning Keynote with Swami Sivasubramanian
• re:Invent 2020 Liveblog: Machine Learning Keynote
• AWS re:Invent 2020 Machine Learning Keynote Recap & Highlights

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.

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

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