{"id":740,"date":"2021-01-08T20:11:36","date_gmt":"2021-01-08T20:11:36","guid":{"rendered":"https:\/\/machine-learning.webcloning.com\/2021\/01\/08\/artificial-intelligence-and-machine-learning-continues-at-aws-reinvent\/"},"modified":"2021-01-08T20:11:36","modified_gmt":"2021-01-08T20:11:36","slug":"artificial-intelligence-and-machine-learning-continues-at-aws-reinvent","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2021\/01\/08\/artificial-intelligence-and-machine-learning-continues-at-aws-reinvent\/","title":{"rendered":"Artificial intelligence and machine learning continues at AWS re:Invent"},"content":{"rendered":"
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A fresh new year is here, and we wish you all a wonderful 2021. We signed off last year at AWS re:Invent<\/a> on the artificial intelligence (AI) and machine learning (ML) track with the first ever machine learning keynote<\/a> and over 50 AI\/ML focused technical sessions covering industries, use cases, applications, and more. You can access all the content for the AI\/ML track on the AWS re:Invent website<\/a>. But, the exciting news is we\u2019re not done yet. We\u2019re kicking off 2021 by bringing you even more content for AI and ML through a set of new sessions that you can stream live starting Jan 12, 2021. Each session will be offered multiple times, so you can find the time that works best for your location and schedule.<\/p>\n

And of course, AWS re:Invent<\/a> is free. Register now if you have not already and build your schedule from the complete agenda<\/a>. Here are some sample sessions from the AI\/ML track that will stream live starting next week<\/p>\n

Here are a few sample sessions that will stream live starting next week.<\/p>\n

Customers using AI\/ML solutions from AWS<\/h2>\n

A day in the life of a machine learning data scientist at J P Morgan Chase (AIM319)<\/strong><\/h3>\n

Thursday, January 14 \u2013 8 AM to 8:30 AM PST<\/p>\n

Thursday, January 14 \u2013 4 PM to 4:30 PM PST<\/p>\n

Friday, January 15 \u2013 12 AM to 12:30 AM PST<\/p>\n

Learn how data scientists at J P Morgan Chase use custom ML solutions built on top of Amazon SageMaker<\/a> to gather intelligent insights, while adhering to secure control policies and regulatory requirements.<\/p>\n

Streamlining media content with PBS (AIM318)<\/strong><\/h3>\n

Wednesday, January 13 \u2013 3 PM to 3:30 PM PST<\/p>\n

Wednesday, January 13 \u2013 11 PM to 11:30 PM PST<\/p>\n

Thursday, January 14 \u2013 7 AM to 7:30 AM PST<\/p>\n

Enhancing the viewer experience by streamlining operational tasks to review, search, and analyze image and video content is a critical factor for the media and entertainment industry. Learn how PBS uses Amazon Rekognition<\/a> to build relevant features such as deep content search, brand safety, and automated ad insertion to get more out of their content.<\/p>\n

Fraud detection with AWS and Coinbase (AIM320)<\/strong><\/h3>\n

Thursday, January 14 \u2013 10:15 AM to 10:45 AM PST<\/p>\n

Thursday, January 14 \u2013 6:15 PM to 6:45 PM PST<\/p>\n

Friday, January 15 \u2013 2:15 AM to 2:45 AM PST<\/p>\n

Among many use cases, ML helps mitigate a universally expensive problem: fraud. Join AWS and Coinbase to learn how to detect fraud faster using sample datasets and architectures, and help save millions of dollars for your organization.<\/p>\n

Autonomous vehicle solutions with Lyft (AIM315)<\/strong><\/h3>\n

Wednesday, January 13 \u2013 2 PM to 2:30 PM PST<\/p>\n

Wednesday, January 13 \u2013 10 PM to 10:30 PM PST<\/p>\n

Thursday, January 14 \u2013 6 AM to 6:30 AM PST<\/p>\n

In this session, we discuss how computer vision models are labeled and trained at Lyft using Amazon SageMaker Ground Truth<\/a> for visual perception tasks that are critical for autonomous driving systems.<\/p>\n

Modernize your contact center with AWS Contact Center Intelligence (CCI) (AIM214)<\/strong><\/h3>\n

Tuesday, January 12 \u2013 1:15 PM to 1:45 PM PST<\/p>\n

Tuesday, January 12 \u2013 9:15 PM to 9:45 PM PST<\/p>\n

Wednesday, January 13 \u2013 5:15 AM to 5:45 AM PST<\/p>\n

Improve the customer experience with reduced costs using AWS Contact Center Intelligence<\/a> (CCI) solutions. You will hear from SuccessKPI, an AWS partner, on how they use CCI solutions to solve business problems such as improving agent effectiveness and automating quality management in enterprise contact centers.<\/p>\n

Machine learning concepts with AWS<\/h2>\n

Consistent and portable environments with containers (AIM317)<\/strong><\/h3>\n

Wednesday, January 13 \u2013 8:45 AM to 9:15 AM PST<\/p>\n

Wednesday, January 13 \u2013 4:45 PM to 5:15 PM PST
Thursday, January 14 \u2013 12:45 AM to 1:15 AM PST<\/p>\n

Learn how to build consistent and portable ML environments using containers with AWS services such as Amazon SageMaker<\/a> and Amazon Elastic Kubernetes Service<\/a> (Amazon EKS) across multiple deployment clusters. This session will help you build these environments with ease and at scale in the midst of the ever-growing list of open-source frameworks and tools.<\/p>\n

Achieve real-time inference at scale with Deep Java Library (AIM410)<\/strong><\/h3>\n

Thursday, January 14 \u2013 3:30 PM to 4 PM PST<\/p>\n

Thursday, January 14 \u2013 11:30 PM to 12 AM PST<\/p>\n

Friday, January 15 \u2013 7:30 AM to 8 AM PST<\/p>\n

Deep Java Library (DJL)<\/a> from AWS helps you build ML applications without needing to learn a new language. Learn how to use DJL and deploy models including BERT in the DJL model zoo to achieve real-time inference at scale.<\/p>\n

Don\u2019t miss out on all the action. We look forward to seeing you on the artificial intelligence and machine learning track. Please see the re:Invent agenda<\/a> for more details and to build your schedule.<\/p>\n

\n

About the Author<\/h3>\n

\"\"Shyam Srinivasan<\/strong> is on the AWS Machine Learning marketing team. He cares about making the world a better place through technology and loves being part of this journey. In his spare time, Shyam likes to run long distances, travel around the world, and experience new cultures with family and friends.<\/p>\n<\/p><\/div>\n","protected":false},"excerpt":{"rendered":"

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