In this talk Laura will go through the theory and practice of time series analysis with examples in R covering concepts such as lag, serial correlation and Box-Ljeung tests. She'll focus on the practical applications of time series analysis and show how data can be modelled using libraries such as xts, zoo and forecast to make predictions on markets and seasonal behaviours. In addition Laura will cover an introduction to deep learning and specifically how Recurrent Neural Networks (RNNs) and LSTM's can be used to make time series predictions with R's RNN package and Tensorflow.
R