As told before, every Sunday a new topic related to probability later also about other ML and data science related topics would also be coming up. This is the second part of the basic of the probability where we will cover mainly the conditional independence and the Bayes rule with a really cool problem at the end.
I am really glad to study this series trying my best to complete the full mathematics and statistics for machine learning for beginners, starting from the probability to stats, linear algebra, calculus, optimization theory, in a full byte sized form (with well furbished hand written notes ). It may take a lot of time, but I guess readers here would collaborate with me, and also please comment so that I can improve more in the next time.
I really assume that readers here know the basics of probability and sets i.e. what is probability, how to find the probability of…
By Anindyadeep Sannigrahi
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This is very much detailed tutorial on the Neural Networks
18 years old guy Mathematics , deep learning, machine learning, beats and music , and some fun , is what all about... our life's reinforcement learning...