Feature Engineering Bookcamp

7 Time series analysis: Day trading with machine learning

This chapter covers

• Working with time series data
• Constructing a custom feature set and response variable, using standard time series feature types
• Tracking intraday profits from our ML pipeline
• Adding domain-specific features to our dataset to enhance performance
• Extracting and selecting features to minimize noise and maximize latent signal

We have been through a lot together, from tabular data to bias reduction to text and image vectorization. All of these datasets had one major thing in common: they were all datasets based on a snapshot in time. All of the people represented in the COMPAS dataset had their data aggregated before we started our analysis. All of the tweets were already ...