AWS Innovate - AI/ML Edition 2021 On-Demand
AI/ML State of the Nation [Keynote]
Innovation is Never Normal [Level 100]
For businesses working with AI and ML however, living this never normal is simply ‘business as usual’, where constant change offers abundant opportunities to innovate, and thrive.
Amazon.com's use of AI/ML to Enhance the Customer Experience
In this session, we share specific examples from Amazon.com's consumer/retail and other businesses to explain how AI/ML helps Amazon deliver the best customer experience possible.
Strategies to Accelerate AI/ML at Scale: From Idea to POC and Achieve Business Outcomes
Learn how executives and managers who are looking to achieve success using ML to accelerate innovation and drive technological progress.
Canada as a Global Leader in AI/ML
This session walks technology leaders through the largest Canadian influences to AI/ML including the latest Canadian investment by AWS in this space.
Offer Your Customers Real-Time Personalized Recommendations
With no prior machine learning experience you can start creating A/B tests to see the impact of Amazon Personalize on increasing user engagement with your recommended products and content.
Overcome Document Processing and Analysis Challenges at Scale
Discover how using Amazon Textract, Amazon Comprehend, and Amazon Augmented AI provide organizations with a machine learning solutio to overcome document processing and analysis at scale.
AWS Security: Where We’re Going and Where We've Been
Here the latest security updates in the Well-Architected categories of detection, identity management, data protection, and incident response.
Intelligent Search to Improve Workforce Productivity
This session will provide a high level overview of cognitive search, why it's important, and what it can do for your customers and employees.
Bring the Power of Machine Learning to Your Fight Against Online Fraud
Take a deep dive into Amazon Fraud Detector, its use cases in your business, and how to quickly get started.
Well-Architectured Framework for Machine Learning
In this whiteboarding session, learn how to design an ML application guided by the AWS Well-Architected Framework five pillars.
Prepare your Datasets at Scale using Apache Spark and SageMaker Data Wrangler [Level 300]
Discover ways to use Apache Spark on AWS to analyze large datasets, perform data quality checks, transform raw data into machine learning features, and train predictive models.
Orchestrate and Automate Machine Learning Workflows with SageMaker Pipelines [Level 300]
In this session, you'll see how to create, automate, and manage end-to-end ML workflows using Amazon SageMaker Pipelines.
Comparing Models in Production with Multi-Armed Bandits and Reinforcement Learning [Level 300]
Using the popular Hugging Face Transformers open source library for BERT to train and deploy multiple natural language understanding (NLU) models.
Reduce Training Time and Cost with SageMaker Debugger [Level 300]
In this session, we walk through how to use the real-time training metrics and set up alerts so you can reduce troubleshooting time, training costs and improve model quality.
Standardize and Automate your Feature Engineering Workflows with SageMaker Feature Store [Level 300]
Learn how to solve all these problems with Amazon SageMaker Feature Store, and how to use it with both the SageMaker Studio user interface and the SageMaker SDK.
Scale your Large Distributed Training Jobs with Data and Model Parallelism Optimized for Amazon SageMaker [Level 300]
In this session, explore how to choose the proper instance for ML training and inference based on model size, complexity, throughput, framework choice, inference latency and portability requirements.
Detect Potential Bias in your Datasets and Explain how your Models Predict using SageMaker Clarify (Level 300)
Select the Right ML Instance for your Training and Inference Job (Level 300)
Automate Code Reviews, Performance Recommendations and Operational Insights (Level 300)