Automatic Revenue Forecasting with Boosting Models and DL
summary
Covers forecasting complex time-series turnover using gradient boosting models and deep learning. Addresses the mathematics of modeling complex dependencies, effective neural architectures for time-series prediction, and ensembling of boosting and deep-learning approaches.
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chapters (9)
- 0:00Introduction
- 3:19ML solution development
- 16:52Project revenue forecasting
- 21:25Time series models
- 25:38Final company solution
- 33:47Post-processing and visualization
- 36:12Neural network optimization
- 41:31Model application and business results
- 44:46Q&A
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