Machine Learning Algorithms In Layman’s Terms, Part 1 (i.e. how to explain machine learning algorithms to your grandma) As a recent graduate of the Flatiron School’s Data Science Bootcamp, I’ve been inundated with advice on how to ace technical interviews. A soft skill that keeps coming to the forefront is the ability to explain complex machine learning algorithms to a non-technical person. This series of posts is me sharing with the world how I would explain all the machine learning topics I come across on a regular basis...to my grandma. Some get a bit in-depth, others less so, but all I believe are useful to a non-Data Scientist. The topics in this first part are: Gradient Descent / Line of Best Fit Audrey Lorberfeld Follow Mar 2 · 14 min read • https://wordstream‑files‑prod.s3.amazonaws.com/s3fs‑public/machine‑ learning.png Linear Regression (includes regularization) Logistic Regression In the upcoming parts of this series, I’ll be going over: Decision Trees R
