Mathematics for ML Specialization

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

Description for Mathematics for ML Specialization

Features of Course

  • 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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