Mathematics for Machine Learning

Completed by Janine Swarbrick

May 24, 2024

Approximately 1 months at 10 hours a week to complete

Course Certificates Completed

Mathematics for Machine Learning: Linear Algebra

Mathematics for Machine Learning: Multivariate Calculus

Mathematics for Machine Learning: PCA

Mathematics for Machine Learning

Imperial College London

4.6 (12,922 ratings)

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220K Students Enrolled

View certificate for Janine Swarbrick, Mathematics for Machine Learning, offered through Coursera. A sequence of 3 courses on the prerequisite mathematics for applications in data science and machine learning. Successful participants learn how to represent data in a linear algebra context and manipulate these objects mathematically. They are able to summarise properties of data sets and map them onto lower dimensional spaces with principal component analysis. Finally they can solve optimisation problems and use this skill to train models for describing data such as simple neural networks.

Course Certificates

Earned after completing each course in the Specialization

Mathematics for Machine Learning: Linear Algebra

Imperial College London

Taught by: David Dye, Samuel J. Cooper & A. Freddie Page

Completed by: Janine Swarbrick by March 22, 2024

5 weeks of study, 2-5 hours/week

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Mathematics for Machine Learning: Multivariate Calculus

Imperial College London

Taught by: Samuel J. Cooper, David Dye & A. Freddie Page

Completed by: Janine Swarbrick by April 26, 2024

6 weeks of study, 2-5 hours/week

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Mathematics for Machine Learning: PCA

Imperial College London

Taught by: Marc Peter Deisenroth

Completed by: Janine Swarbrick by May 24, 2024

4 weeks of study, 4-6 hours/week

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