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High-Performance Time Series Forecasting in R & Python

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Sep 17, 2020
1:19:30

Time series is changing. The demands are greater. Companies now demand scalable & automated forecasting systems that can handle forecasting 10,000+ time series daily or weekly. This is challenging data scientists to adapt to meet the demand. Learn these skills and become invaluable to your organization, accelerating your career in the process. Here's the playbook for accelerating your career. PLAYBOOK ===== ✅ Agenda 1:48 ✅ The BIG CHANGE 3:34 ✅ The 3 PROPERTIES of High-Performance Forecasting Systems 9:40 ✅ COMPETITION RESEARCH - What Forecasting Technologies get RESULTS 13:05 ✅ 5 COMPETITION TAKEAWAYS 21:44 ✅ MACHINE LEARNING RESEARCH - Modeltime 24:34 ✅ WHAT ABOUT FEATURE ENGINEERING? - Timetk 30:35 ✅ WHAT ABOUT DEEP LEARNING? - GluonTS 34:17 ✅ WHAT ABOUT SCALABILITY? - Future 36:39 ✅ FORECASTING CHEAT SHEET - This cheatsheet is so valuable 38:22 ✅ NEW TIME SERIES COURSE - 43:35 ✅ [SPECIAL OFFER] 56:27 COURSES ==== 1. 5-Course R-Track Program: https://university.business-science.io/p/5-course-bundle-machine-learning-web-apps-time-series 2. High-Performance Time Series Forecasting (DS4B 203-R): https://university.business-science.io/p/ds4b-203-r-high-performance-time-series-forecasting/ #timeseries #forecast

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