Chapter 10: Exploring Time Series Analysis
In the previous chapter, we discussed using deep learning and its robust applicability when it comes to unstructured data in the form of natural language – a type of sequential data. Another type of sequential data that we will now turn our attention to is time series data. We can think of time series data as being standard datasets yet containing a time-based feature, thus unlocking a new set of possibilities when it comes to developing predictive models.
One of the most common applications in time series data is a process known as time series analysis. We can define time series analysis as an area of data exploration and forecasting in which datasets are ordered or indexed using a particular time interval or timestamp. There are many examples of time series data that we encounter in the biotechnology and life sciences industries daily. Some of the more laboratory-based areas of focus include gene expression and chromatography,...
