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.
Guest Speakers: Andrew Zhang
Topics: Operationalizing the Machine Learning Pipeline
Data Scientists and ML Practitioners need more than a Jupyter notebook to build, test, and deploy ML models into production. They also need to ensure they perform these tasks in a reliable, flexible, and automated fashion. There are three basic questions that should be considered when starting the ML journey to develop a model for a real Business Case:
1. How long would it take your organization to deploy a change that involves a single line of code?
2. How do you account for model concept drift in production?
3. Can you build, test and deploy models in a repeatable, reliable, and automated way?
So, if you’re not happy with your answers to these questions, then MLOps is a concept that can help you to:
1. Create or improve the organization culture and agility for Continuous Integration/Continuous Delivery (CI/CD).
2. Create an automated infrastructure that will support your processes to operationalize your ML model.
In this talk, we’ll walk through an MLOps pipeline that automates the typical procedures used by ML Practitioners, namely the CRISP-DM process. In essence, we will automate these often manual processes, such as data pre-processing, feature engineering, model training, model testing, model deployment, and model monitoring by creating a CI/CD pipeline. All using the agile DevOps best practices.
Andrew Zhang, Sr. Manager, Amazon Web Services
About Data Application Lab:https://www.dataapplab.com/about-us/
About IDEAS: https://www.ideassn.org/