Home AI Courses Mathematics for ML: Multivariate Calculus

Mathematics for ML: Multivariate Calculus

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This course offers a concise summary of essential multivariate calculus for machine learning, including practical tools, vector calculations, function approximation, and neural network applications, to build confidence for advanced studies.

Key AI Functions:Linear Regression,Vector Calculus,Multivariable,Calculus Gradient,Descent

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Description for Mathematics for ML: Multivariate Calculus

Features of Course

This course provides a succinct summary of the multivariate calculus necessary for the development of common machine learning techniques, ranging from fundamental slope concepts to formal gradient definitions.

Create a collection of calculus instruments, acquire the ability to calculate vectors on multidimensional surfaces, and apply this knowledge through interactive activities.

Investigate the application of calculus to approximate functions and evaluate the precision of these approximations, as well as its role in neural network training.

Acquire a thorough comprehension of calculus and the requisite language to conduct independent research, thereby fostering confidence for more advanced machine learning courses.

Level: Beginner

Certification Degree: Yes

Languages the Course is Available: 22

Offered by: On Coursera provided by Imperial College London

Duration: 17 hours (approximately)

Schedule: Flexible

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