IDEAS Online Free Webinar
IDEAS & Data Application Lab co-host this live webinar.
IDEAS is a global nonprofit organization that is dedicated to fostering the data engineering and data science ecosystems and broadening the adoption of their underlying technologies to accelerate the innovations data can bring to society. Our goal is to create a community to connect AI and Data Science enthusiasts. All of the conferences that IDEAS host will demonstrate cutting-edge technology and feature a variety of AI and Data Science experts covering topics including industry trends, real-world applications, open-source software, solutions-based case studies, and many others.
Topics: Automating Production Level Machine Learning on AWS
Machine Learning (ML) has revolutionized how we’ve solved business problems over the last decade. The ability to collect and store limitless data, coupled with advancements in computing and networking, has led to the use of Machine Learning in many business verticals.
However, developing end to end machine-learning pipelines and workflows that provide continuous and adaptive business insights to other applications or users is a challenge. This is primarily because of an inherent gap in how data scientists develop the machine learning models and how ML operations teams promote and deploy them into the production environments. Furthermore, complexities of CI/CD in the ML context, such as model governance and quality assessment, distinguish ML Ops from traditional DevOps. We will explore these specific challenges, and illustrate how familiar cloud services can be stitched together to bridge this gap between development and deployment, and to address the specific needs of ML Ops. The overall architecture pattern of a “model factory” enables support for numerous machine learning models in production and development simultaneously along with CI/CD for data science and automated workflows for Development, QA, and Production.
Mark McQuade is an AWS and Cloud-Based Solution Specialist, Knowledge Addict, Relationship Builder, and Practice Manager of Data Science & Engineering at Onica. His passion is in the data, artificial intelligence, and machine learning areas. he also loves promoting AWS data and ML services through webinars and events and passing my knowledge and passion onto others.
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