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

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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