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Mathematics for ML Specialization

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Machine learning mathematics. Find out about the mathematical prerequisites for applications in machine learning and data science.

Key AI Functions:Eigenvalues And Eigenvectors,Principal Component Analysis (PCA),Multivariable Calculus,Linear Algebra

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Description for Mathematics for ML Specialization

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This specialization bridges the gap between fundamental mathematics and its application in Machine Learning and Data Science, fostering an intuitive understanding and connection to these fields.

The initial course covers linear algebra, including the definitions and manipulation of vectors and matrices, and their relationship to data.

The second course on multivariate calculus focuses on optimizing data fitting functions, building on the linear algebra concepts from the first course.

The third course on dimensionality reduction with Principal Component Analysis uses the mathematics from the first two courses to compress high-dimensional data, requiring proficiency in Python and numpy, and includes practical mini-projects using Python on interactive notebooks.

Level: Beginner

Certification Degree: Yes

Languages the Course is Available: 22

Offered by: On Coursera provided by Imperial College London

Duration: 1 month at 10 hours a week

Schedule: Flexible

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