Author(s: Juv Chan Original publication on , the World’s Most Reputable AI and Technology News and Media Company. We invite you to become an AI sponsor if you’re working on an AI product or service. helps technology and AI startups scale. We can help you bring your technology to everyone. Artificial Intelligence image by p2722754, Pixabay. As a re:Invent participant, there are many AI/ML sessions available to you. There are more than 100 AI/ML session at re:Invent . Here are some hidden gems that AI/ML sessions can offer. Accelerate innovation using machine learning (AIM 212-L). Hear Bratin Saha from AWS, Vice President for Machine Learning & Engines, and Kimberly Madia from Amazon AI at AWS discuss how AWS AI & ML services can help customers innovate faster, e.g. Making more precise predictions and gaining deeper insight from customers’ data. This helps to reduce operational overhead, improve customer experience, and lower operating costs. Amazon Personalize ML allows you to create outstanding user experiences (AIM 204) Amazon Personalize) ML allows users to add personalized recommendations. It can be used for personalised recommendations, such as giving recommendations based upon their behavior and preferences, personalizing results and customizing emails. Amazon Personalize can be used to create personalized recommendations for product and content. This will increase engagement and retention and help you to make your customers more engaged. Amazon SageMaker’s Vanguard (AIM 320) MLOps (Machine Learning Operations), enables continuous and automatic delivery of ML production loads. To optimize production lead times and other operational metrics for their ML workload, more organizations use or plan to use MLOps. MLOps helps machine learning engineers, data scientists and DevOps professionals collaborate in the preparation, building, training, deployment, management, and maintenance of large-scale models via pipelines and automated workflows. Vanguard shares their experience in implementing MLOps to attain ML at scale using their multilingual model development platforms. This includes SageMaker projects and SageMaker Pipelines. SageMaker Model Registry. SageMaker Model Monitor. Achieve cost-effective and high-performance model deployment (AIM Performance optimization and cost optimization are the two pillars of AWS Well-Architected Framework. These pillars represent how computing resources can be used efficiently to satisfy system requirements, deliver business value and meet the lowest possible price. Goldman Sachs explains how Amazon SageMaker is used to deliver relevant content recommendations and fast low-latency ML model deployments. Bloomberg invests in smarter search using Amazon Kendra (AIM 206) Amazon Kendra) is an intelligent search engine powered by machine-learning that allows your users to search structured data with natural language. Amazon Kendra makes use of machine learning to provide more pertinent answers from unstructured information and continuously improve search results, based on user feedback. Learn how Bloomberg utilized Amazon Kendra for a ML-based search engine that targeted a particular content set. They also share their knowledge of working with Amazon API Gateway and AWS Lambda. Find Hidden Gems in AI/ML Sessions at AWS re-Invent This story was first published on Medium by . People are responding and highlighting this article. Get the AI newsletter and join thousands of data professionals. We don’t spam and it’s completely free. Stay up-to-date with AI news. Research, projects and new ideas. We invite you to become a sponsor if you’re building an AI startup or an AI-related service. Published via
Explore Hidden Gems in AI/ML Sessions at AWS reInvent 2021
