AWS DeepRacer is a fun and easy way for developers with no prior experience to get started with machine learning (ML). At the end of the 2019 season, the AWS DeepRacer League engaged the Amazon ML Solutions Lab to develop a new sports analytics feature for the AWS DeepRacer Championship Cup at re:Invent 2019. The purpose for these real-time analytics was to provide context and more in-depth experience with top competitors' strategies and tactics. This helped viewers tangibly interpret how specific model strategy translated to on-track performance, which further demystified ML development and demonstrated its real-world application. This enhancement enabled fans to monitor the performance and driving style of competitors from around the world.

Typical approaches to automatic ML don't provide insights into the data or logic used to create models, forcing you to compromise on accuracy. Join us as we introduce Amazon SageMaker Autopilot, an automated capability that generates ML models and provides complete control and visibility of them. Learn how Autopilot automatically inspects raw data, picks the best set of algorithms, trains multiple models, tunes them, and ranks them based on performance. The result is a recommendation for the best performing model and visibility into the logic and code for how the model was created and what's in it. Autopilot offers the best combination of automatic model creation with control and visibility.

Amazon SageMaker helps provide the best model performance for less cost. In this session, we walk through a TCO analysis of Amazon SageMaker, exploring its three modules--build, train, and deploy. Learn how Amazon SageMaker automatically configures and optimizes ML frameworks such as TensorFlow, MXNet, and PyTorch, and see how to use pre-built algorithms that are tuned for scale, speed, and accuracy. We explain how the automatic model tuning feature performs hyperparameter optimization by discovering interesting features in your data and learning how those features interact to affect accuracy. We end by showing how Aramex uses Amazon SageMaker.

Doubtless there will be some kind of machine learning update, but what it is could depend on what AWS customers have innovated. Last year the company announced a partnership with NFL app Next Gen Stats, the automation of NASCAR's video library and multiple services with US-based ride-hailing firm Lyft. Vegas is all about gambling, but it's a safe bet that at least one of these companies will be in attendance to talk through case studies.

Doubtless there will be some kind of machine learning update, but what it is could depend on what AWS customers have innovated. Last year the company announced a partnership with NFL app Next Gen Stats, the automation of NASCAR's video library and multiple services with US-based ride-hailing firm Lyft. Vegas is all about gambling, but it's a safe bet that at least one of these companies will be in attendance to talk through case studies.

With less than a week to go, the excitement and anticipation are building up for industry's largest cloud computing conference - AWS re:Invent. As an analyst, I have been attempting to predict the announcements from re:Invent (2018, 2017) with decent accuracy. But with each passing year, it's becoming increasingly tough to predict the year-end news from Vegas. Amazon is venturing into new areas that are least expected by the analysts, customers, and its competitors. AWS Ground Station is an example of how creative the teams at Amazon can get in conceiving new products and services.

With less than 40 days to re:Invent 2019, the excitement is building up and we are looking forward to seeing you all soon! Continuing our journey on artificial intelligence and machine learning, we are bringing a lot of technical content this year, with over 200 breakout sessions, deep-dive chalk talks, hands-on exercises with workshops featuring Amazon SageMaker, AWS DeepRacer, and deep learning frameworks such as TensorFlow, PyTorch, and more. You'll hear from many customers including Vanguard, BBC, Autodesk, British Airways, Fannie Mae, Thermo Fisher, Intuit, and many more. We are also hosting the Machine Learning Summit again this year, where you will hear from researchers and entrepreneurs about the latest breakthroughs today and the future possibilities tomorrow. To get you started on planning, here are a few highlights for the AI and ML sessions from the re:Invent 2019 session catalog.

The Machine Learning Summit is designed for everyone from data scientist to business professionals. If you've ever been curious about artificial intelligence and machine learning, whether you're just getting started on your machine learning journey or already a machine learning practitioner, this Summit will provide you with knowledge of what's on the horizon for machine learning. To attend the Machine Learning Summit, purchase a ticket to AWS re:Invent 2019. Once reserved seating opens in the fall, you will be able to register for a seat.

The AWS DeepRacer League is the world's first global autonomous racing league. There are races at 21 AWS Summits globally and select Amazon events, as well as monthly virtual races happening online and open for racing. No matter where you are in the world or your skill level, you can join the league. Get a chance to win AWS DeepRacer cars and the top prize of an all-expenses-paid trip to re:Invent 2019, to compete in the AWS DeepRacer Championship Cup. The competition is heating up as the Summit Circuit hit the halfway mark in Sweden this week.