Polynomial regression with sklearn as an introduction to machine learning with python.
To follow through the example, just copy the contents of the init.py file from GitHub and execute it in a separate file on your current PC. Make sure to run init.py in a directory where you want to store your code, for example I would store it in the Desktop directory. Init.py will initialize a new tutorial directory called "ml_101" with main.py and the necessary data for the example. It will delete itself after it has been executed on the python interpretor. Make sure numpy, pandas, matplotlib, and sklearn libraries are installed on the environment.
Problem: You are contracted to assassinate a wanted felon as part of the government's covert operations. You were supplied with a rifle that fires subsonic ammunition that travels 335 meters/second. Due to the slow muzzle velocity of subsonic rounds, you would have to compensate considerably for bullet drop. The assigned vantage point is roughly 150 meters away from the target. Using ballistics data provided, come up with a machine learning model that can predict the bullet drop in order to hit an accurate shot on the felon.
** This is a made up problem for the purpose of mimicking a somewhat real life scenario.