Multiple Independent Observations — Topic 96 of Machine Learning Foundations

#MLFoundations #Probability #MachineLearning In this video, we consider probabilistic events where we have multiple independent observations — such as flipping a coin two or more times instead of just once. There are eight subjects covered comprehensively in the ML Foundations series and this video is from the fifth subject, “Probability & Information Theory“. More detail about the series and all of the associated open-source code is available at The playlist for the Probability subject is here: Jon Krohn is Chief Data Scientist at the machine learning company Nebula. He authored the book Deep Learning Illustrated, an instant #1 bestseller that was translated into seven languages. He is also the host of SuperDataScience, the industry’s most listened-to podcast. Jon is renowned for his compelling lectures, which he offers at Columbia University, New York University, leading industry conferences, and online via O’Reilly. More cours