figure - deriving elapsed time difference from current time based on our computationseach new derived feature should give us the elapsed time difference between the current time and the time value in the time column (actually timeutc since conversion to utc is necessaryboth the values are almost equal to one anotherwhich is expected thus you can use time and date arithmetic to extract and engineer more features which can help build better models alternate time representations enable you to do date time arithmetic directly instead of dealing with specific api methods of timestamp and datetime objects from python however you can use any method to get to the results you want it' all about ease of use and efficiencyfeature engineering on image data another very popular format of unstructured data is images sound and visual data in the form of imagesvideoand audio are very popular sources of data which pose lot of challenge to data scientists in terms of processingstoragefeature extraction and modeling however their benefits as sources of data are quite rewarding especially in the field of artificial intelligence and computer vision due to the unstructured nature of datait is not possible to directly use images for training models if you are given raw imageyou might have hard time trying to think of ways to represent it so that any machine learning algorithm can utilize it for model training there are various strategies and techniques that can be used in this case to engineer the right features from images one of the core principles to remember when dealing with images is that any image can be represented as matrix of numeric pixel values with that thought in mindlet' get startedyou can load feature_engineering_image py directly and start running the examples or use the jupyter notebookfeature engineering on image data ipynbfor more interactive experience let' start by loading the necessary dependencies and configuration settings in [ ]import skimage import numpy as np import pandas as pd import matplotlib pyplot as plt from skimage import io %matplotlib inline the scikit-image (skimagelibrary is an excellent framework consisting of several useful interfaces and algorithms for image processing and feature extraction besides thiswe will also leverage the mahotas frameworkwhich is useful in computer vision and image processing open cv is another useful framework that you can check out if interested in aspects pertaining to computer vision let' now look at ways to represent images as useful feature vector representations