Exercises on Event Probabilities — Topic 98 of Machine Learning Foundations
#MLFoundations #Probability #MachineLearning
In my series of videos on Probability Theory we’ve already covered events, sample spaces, multiple observations, and combinatorics. This video features four exercises — some using paper and pencil, some using Python code — to test and cement your understanding of the topics so far.
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.