Predicting Failures from Sensor Data using AI/ML -- Part 2 - Open Source Leader in AI and ML

This is Part 2 of the blog post series and continuation of the original post, Predicting Failures from Sensor Data using AI/ML -- Part 1. One of the things to note is that the hard-disk data set has a lot of missing values across its columns. Check out the Missing Data Heat Map on the training data set -- Derived from Auto-Viz in Driverless AI. From the picture below, one can tell that a majority of sensor data is missing or incomplete – the red color in the aggregated chart indicates missing data. Where it's incomplete, one can easily guess, it might be that not all hard-disk vendors agree to generate sensor data for a S.M.A.R.T sensor variable. When I tried to build a base AI/ML model in Driverless AI, I got a notification that it automatically dropped these 19 columns because of empty or constant values.