Explore the inner workings of key machine learning algorithms and methods in this comprehensive 1.5-hour video lecture from the End to End Machine Learning course. Gain a deep understanding of decision trees, Bayes Theorem, autocorrelation, Support Vector Machines, and k-nearest neighbors. Learn how to open the "black box" of machine learning models and grasp the fundamental concepts behind these powerful tools used in signal processing and statistics.
Overview
Syllabus
How decision trees work.
How Bayes Theorem works.
How autocorrelation works.
How Support Vector Machines work / How to open a black box.
How k-nearest neighbors works.
Taught by
Brandon Rohrer
