Let's look at two ways to get the answers: I'm not sure if I knew this when I wrote the questions, but the opening Wikipedia page has the answers. The entropy is zero: each toss of the coin delivers no new information as the outcome of each coin toss is always certain. a double-headed coin that never comes up tails, or a double-tailed coin that never results in a head. and to communicate the outcome of a coin flip (2 possible values) will require an average of at most 1 bit ( exactly 1 bit for a fair coin). If you then jump over to (information_theory), it even has the answers: The term and the concept are used in diverse fields, from classical thermodynamics, where it was first recognized, to the microscopic description of nature in statistical physics, and to the principles of information theory. What is entropy?Įntropy is a scientific concept, as well as a measurable physical property that is most commonly associated with a state of disorder, randomness, or uncertainty. So I'm writing this post to remind and excite ourselves about entropy. I find entropy to be one of the most intellectually pleasing concepts, partially because it occurs across a wide array of disciplines.I learned about entropy in multiple classes during my Physics degree (20 years ago).I learned about entropy in multiple classes during my Comp.Sci.Our current datascience-main git repo has 7 occurences of the string entropy in our own code (not library code). Entropy is a common and useful concept in Data Science.So, why did I think these are good and relevant screening questions? My recruiter reports that from a sample size of ~50 candidates, very few can answer these entropy related questions. Q: What is the entropy of a coin that is almost always heads? A: 0 bits (or approximately 0 bits) Q: What is the entropy of a fair coin toss? A: 1 bit The questions are asked by my (non-technical) recruiter on the phone, so I wrote them so they have objective answers, like yes/no/0/1/42. I use a set of 20 screening questions for Data Science interviews.
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