Introducing The DataHour Series – Webinars with Industry Leaders

Sakshi Khanna 16 Feb, 2022 • 3 min read

Introduction

The word community has become a buzzword across the globe. Businesses have realized the power of community-led growth and are heavily invested in building and continuously giving to the audience. Well..guess what? At Analytics Vidhya, the community has been at the forefront since its inception with aim of building the best AI ML ecosystem any company can offer.

With a Leading community knowledge portal, our ecosystem is magnifying at a 3x speed. Keeping the community in mind, we are happy to announce that we have launched a webinar series: The DataHour. The webinars will be led by top industry leaders which will help us to enable deeper discussions and conversations with our cherished community.

The Data Hour

Highlights

Below are various highlights of the webinar series

Lead by Top Industry Leaders
Duration: 60 to 80 mins
Learn Tools and Techniques in the Data Science Domain
Hands-on Learning
Free to Attend
Recordings will be available later

Our webinar series: The DataHour is definitely going to be a fun way to understand the concepts of Data Science from the Leading Players in the Data Science domain. We are hopeful that these webinar sessions are going to be a great source of enrichment and value-adding for our community members.

Upcoming Webinars: The DataHour

We are enthralled to share that we have two upcoming webinars in the month of February 2022.

15th Feb 2022: An overview of Feature Engineering for Data Science
22nd Feb 2022: Hands-on Workshop on Feature Engineering
25th Feb: Lessons Learned from Hundreds of Machine Learning Projects

About the Webinars

In the 1st webinar, we will discuss advanced feature engineering techniques, best practices for ensuring these techniques work in a production environment, and finally, share a repository of more advanced feature engineering techniques.
In the 2nd second webinar, there is going to be a hands-on workshop in which we’ll walk through the feature engineering process for a modeling problem. We’ll apply advanced feature engineering techniques to a set of transactions to show how they can build a complex picture of behavior over time.
In the 3rd webinar, we will share some important lessons while working and managing data science projects. We will describe how to combine research & execution, how to scale experimentation, reduce the need of labeled data, share features, handle privacy, etc.

Speaker Profiles

An overview of Feature Engineering for Data Science and Hands-on Workshop on Feature Engineering
Andrew Engel,
Chief Data Scientist at Rasgo

Andrew Engel is the Chief Data Scientist at Rasgo. He has been working as a data scientist and leading teams of data scientists for over ten years in a wide variety of domains from fraud prediction to marketing analytics.

Andrew received his Ph.D. in Systems and Industrial Engineering with a focus on optimization and stochastic modeling. He has worked for Towson University, SAS Institute, the US Navy, Websense (now ForcePoint), Stics, HP and led DataRobot’s efforts in Entertainment, Sports, and Gaming before joining Rasgo in August of 2020. He will be taking both the webinars.
Lessons Learned from Hundreds of Machine Learning Projects
Prashant K Dhingra,
Managing Director(Machine Learning), JPMorgan Chase

Prashant K Dhingra is the Managing Director for Machine Learning at JP Morgan Chase. Since 2008 he has worked on a variety of ML models and has a good experience of 28 years. Prior to JPMC, he had worked at Google and Microsoft. At Google, he was the Head of Machine Learning for Manufacturing and Industry. At Microsoft, he worked on Azure ML, Bing, and the SQL Server team. Prashant has also written a book on SQL Server and a chapter on ML in an NOAA book.