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by Jeffrey Yau, Chief Data Scientist, Alliance Bernstein

Given the resurgence of neural network-based techniques in recent years, it is important for data science practitioner to understand how to apply these techniques and the trade-offs between neural network-based and traditional statistical methods. This lecture discusses two specific techniques, real-world applications and their advantages and disadvantages, and demonstrations of exploratory time series data analysis.

Vector Autoregressive (VAR) Models – one of the most important class of multivariate time series statistical models applied in finance. Recurrent Neural Network (RNN) - a neural network architecture suitable for time series forecasting.

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