time series

Time-Series Analysis: Wearable Devices using DTW and kNN

Time-Series Analysis: Wearable Devices using DTW and kNN

Recently, there has been great success in time series analyses by applying dynamic time warping (DTW). Indeed, when combined with simple algorithms such as k-Nearest Neighbours, DTW has reproduced accuracies of  state-of-the-art algorithms, such as deep neural nets etc.

We will discuss here a supervised classification example of wearable devices and a possible use-case for DTW.

 

Predicting Stock Volume with LSTM

Much of the hype surrounding neural networks is about image-based applications. However, Recurrent Neural Networks (RNNs) have been successfully used in recent years to predict future events in time series as well. RNNs have contributed to breakthroughs in a wide variety of fields centered around predicting sequences of events. In this piece, however, we'll demonstrate how one type of RNN, the Long Short-Term Memory (LSTM) network, can be used to predict even financial time series data—perhaps the most chaotic and difficult of all time series.