Modern Time Series Analysis-SOLD OUT
This tutorial will cover the newest and most successful methods of time series analysis. 1. Bayesian methods for time series 2. Adapting common machine learning methods for time series 3. Deep learning for time series These methods are producing state-of-the-art results in a variety of disciplines, and attendees will learn both the underlying concepts and the Python implementations and uses of these analytical approaches to generate forecasts and estimate uncertainty for a variety of scientific time series.
NumPy, Scikit Learn. Students will be best positioned to learn in this tutorial if they have a basic familiarity with (1) statistics (2) machine learning and (3) deep learning fundamentals (4) standard data preprocessing techniques