An Introduction to Time Series Forecasting | Walmart
About This Video
Forecasting using time series data is a hot topic of research and is applied to a variety of use-cases to make important decisions – wherever there are changes with time (seasonal or trend) such as e-commerce orders, stock market prices, weather prediction, demand and usage of products, etc. This workshop will cover time series analysis that attempts to understand the nature of the series and is useful for future forecasting along with the overview of popular forecasting models such as ARIMA, SMA, SES, Prophet followed by a case-study walk-through.
This workshop was conducted by Apurva Sinha & Sinduja Subramaniam at Walmart Global Tech.
In This Video
Staff Data Scientist, Walmart
Apurva is a Data Scientist at Walmart Global Tech in Sunnyvale, California with 6 years of experience in building data driven solutions. She is currently working as part of Data Strategy & Insights team, building a multi-class classification algorithm for assigning shelves to products under Walmart.com, leveraging product attributes. Apurva has a Master’s degree in Business Analytics from The University of Texas, Dallas.
Staff Data Scientist, Walmart
Sinduja is a Staff Data Scientist/Manager at Walmart Global Tech in California with 6+ years of experience in tackling personalization challenges and problems. At Walmart Global Tech, Sinduja is both an independent contributor and manager of a team of data scientists. She leads data and relevance initiatives around customers’ repurchase journey, page-level model design, particularly on the home page. Sinduja has a Master’s degree in Computer Science, specializing in big data and machine learning, from the University of Illinois at Urbana Champaign. She also holds multiple patents..