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Machine Learning Course by Andrew Ng of Stanford University

My work on the course, completed in 2018, an excellent course that gives a fundamental understanding of many of the principles of machine learning, from linear regression, through polynomial, support vector machines, neural networks and PCA, also going on to look at bias, variance, anomaly detetction etc.

The course has you code in Octave/Matlab and avoid higher level languages in order that you understand the work that is done and gain a good grasp of mechanics behind ML, from the matrix operations to the resulting level of computing required.

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