Machine Learning Webinar: Understand The Fundamentals Of Building ML Applications

Key takeaways

Enterprises increasingly rely on machine learning for mission-critical applications.
Building machine learning models involves challenges like data integration and feature engineering.
The webinar targets ML engineers and data scientists, focusing on fundamental ML concepts.
Participants will learn to select algorithms and deploy ML models without deep mathematical insights.
Staying updated with the latest trends is essential for optimal machine learning application performance.

Enterprises are increasingly relying on machine learning to develop mission-critical applications to power their businesses. However, there are a series of challenges one has to tackle in the machine learning application building lifecycle — right from combining multiple data sources to feature engineering which means finding the right parameters to extract from the data for model building. So, what’s the best approach to AI/ML applications and how does one identify the data sources to build models. With demand for machine learning increasing, it’s up to the data scientists and developers to stay updated with the latest trends to get the best performance out of their applications. With machine learning becoming a critical enabler for every sector, this webinar is specifically aimed at machine learning engineers and data scientists to help them understand the fundamental concepts of ML and help them leverage cloud machine learning tools. During the webinar, participants will learn how to select an algorithm, build a ML model and deploy it effectively, without diving too deep into the mathematical concepts of the model. Great Learning presents a webinar on Introduction to Machine Learning by Dr Kumar Muthuraman,Faculty Director, Center for Research and Analytics, University of Texas at Austin who will take the participants through the following areas:

Introduction to Machine Learning
How Machine Learning is changing the world around us
Case study on how Machine Learning is used to solve a business problem
Q&A with the speakers

Who Should Attend:

Data Scientists who wish to speed up and work on machine learning use cases
Software Engineers and machine learning enthusiasts who want to gain deeper insights into machine learning frameworks
ML Engineers and enthusiasts who want to understand the machine learning application development lifecycle
Industry members who want to learn how to leverage ML to meet business objectives

The webinar is presented by Dr. Kumar, who is the H. Timothy (Tim) Harkins Centennial Professor in the Department of Information, Risk and Operations Management and the Department of Finance at McCombs School of Business, University of Texas at Austin. Dr Kumar received his Ph.D. from Stanford University and his research focuses on decision making under uncertainty. Application areas of interest to him are quantitative finance, operations management and health care When: March 17 at 11 am To register click here

Machine Learning Webinar: Understand The Fundamentals Of Building ML Applications

Key takeaways

Stay ahead with AI insights.