Mathematics for Machine Learning: Linear Algebra
Mathematics for Machine Learning: Linear Algebra is one of the Online Courses to Learn Algebra which looks at what linear algebra is and how it relates to vectors and matrices in this Linear Algebra course. Then we'll go through what vectors and matrices are and how to utilize them to solve issues, including the tricky problem of eigenvalues and eigenvectors. Finally, we'll look at how to use these to do fun things with datasets, such as rotating photographs of faces and extracting eigenvectors to investigate the Pagerank algorithm.
You'll create code blocks and use Jupyter notebooks in Python toward the conclusion of the course, but don't worry; these will be brief, focused on the principles, and will walk you through if you've never coded before.
You will have an intuitive knowledge of vectors and matrices at the end of this course, which will help you bridge the gap into linear algebra issues and apply these principles to machine learning.
This course offers:
- Flexible deadlines: Reset deadlines in accordance to your schedule.
- Certificate : Earn a Certificate upon completion
- 100% online
- Beginner Level
- Approx. 19 hours to complete
- Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
- Course 1 of 3 in the Mathematics for Machine Learning Specialization
Coursera Rating: 4.7/5
Enroll here: https://www.coursera.org/learn/linear-algebra-machine-learning
