# Essential Math for Machine Learning: Python Edition

Essential Math for Machine Learning: Python Edition

.MP4, AVC, 1280×720, 30 fps | English, AAC, 2 Ch | 1h 48m | 439 MB

Course by Microsoft General Technical Skills

Core mathematical concepts such as single-variable calculus, multivariable calculus, matrices, and linear algebra are the underpinnings of all machine learning algorithms. And for many professionals with an interest in machine learning and AI, revisiting these concepts can be a bit intimidating. This course demystifies the essential math that you need to grasp-and implement-in order to write machine learning algorithms in Python. Review fundamental algebraic concepts; derivatives and optimization; statistics; and the basics of probability.

Topics include:

Exponentials, radicals, and logarithms

Performing arithmetic operations on polynomials

Rates of change

Using derivatives to analyze functions

Multiplying vectors and matrices

Solving systems of equations with matrices

Visualizing data

Confidence intervals

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