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 github.com/jonkrohn/ML-foundations
The playlist for the Probability subject is here: https://www.youtube.com/playlist?list...
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 courses and content from Jon can be found at jonkrohn.com.