Thursday, 21. March 2019, SAP Tempe, Machine learning for Time Series Forecasting & It's Applications

Description:In this session we will explore Machine Learning for Time Series Forecasting and its application in real-world business scenarios. It will be a great opportunity to visit the SAP office and meet with their Data Scientists.
We will learn several topics including:- Statistical vs Machine Learning techniques for Time Series Forecasting- Understanding of Time series components like Seasonality, Trend, Cycles, Outliers, Lags, etc.- Time Series vs Regression Problems ; Analyzing Forecasting Accuracy- Demo of Time Series Forecasting in SAP Business Applications for Retail Demand Planning, Supply Chain Integrated Business Planning and other Customer Use cases- Supervised Machine Learning and Deep Learning methods for forecasting Time Series data. ARIMA models, Gradient Boosting, LSTM etc.- Optional Python based hands-on exercise on how to forecast and analyze forecast accuracy using Scikit-Learn on a Time Series dataset.

Schedule:6:15-6:45: Food & Networking and tour of SAP Labs6:45-8:00: Presentation, Hands-On-exercises and Q&A8:00-8:15: Wrap-up and "High-Five Everyone Till Next Time"

About the Speakers:Raghav Jandhyala is a Director of Product Management at SAP for Digital Supply Chain. Author of three books on Digital Supply Chain, Raghav has over 16 years of experience in different fields like Supply Chain Management, Retail and Banking along with a strong technical background in Big Data, Cloud and Machine Learning and drives development & adoption of business applications. He has Masters in Computer Science from Southern Illinois University along Advanced Machine learning and AI from Harvard Extension. Raghav works with Strategic Customers for new product innovations and as a trusted advisor for their Business Transformations. Raghav is also a Guest Speaker at ASU WP Carey School of Business and a Mentor at Phoenix Data Science Meetups..
Mike Davis is a developer and data scientist is the Unified Demand Forecast team at SAP. He has been doingmodeling and forecasting at SAP in the retail and banking sectors, and as a consultant for over 15 years. Overall, he had worked developing software in various industries for 33 years. Mike has a bachelor’s degree from Harvard University and has studied mathematics at Massachusetts Institute of Technology. He has lived in Arizona for 23 years.

Machine learning for Time Series Forecasting & It's Applications

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