A Data Scientist/ML Engineer must analyze the data and apply the right model to it, in order to get useful results. Probability and Statistics are two fields of study that can advance one’s such skills.

Therefore, I decided to emphasize on that and write my first article on the Essential probNstats 4 ML project. Its contents are basic probabilistic or statistical concepts, every Data Scientist and ML Engineer should know. Expected value The Expected value of a random variable is the average of that variable. For example given the Variable X = [1, 2, 3, 4, 5, 6] which represents a six-sided die where every side has exactly the same probability of occurrencehe answers I most often get are “Nobody” or “I don’t know.” When I do get a name, it often differs depending on who I asked—a marketing executive points to one person, while finance identifies someone else. That isn’t good. How can analytics become a strategic, core component of an organization if there is no clear owner and leader for analytics at the corporate level?

Source: towardsdatascience.com
Author: Christos Mousmoulas