Missing subjects such as Eigenvector/ eigenvalue
In the last lesson it’s mentioned that we will continue to learn more linear algebra, but the course ends there. Egenvectors and Eigenvalues are also mentioned in the lesson, and they are very important for machine learning theory. I wanted to refresh my math knowledge using 365, but here there are a few things missing
Hi Brenda,
thanks for reaching out! You're absolutely right, Eigenvectors and Eigenvalues are important foundations in Linear Algebra. It's great to learn that you're taking an interest in the topic, and I agree with you, I consider Linear Algebra itself to be fundamental for understanding the field of machine learning.
I'm really happy to say that we're currently working on a follow up course concerning Linear Algebra and Feature Selection, which we'll be releasing in the following months.
We'll be covering eigenvalues and eigenvectors, as well as see dimensionality reduction techniques like PCA and LDA. You can see the full list of topics in the course here:
Upcoming courses | 365 Data Science
I'm really exited to be sharing the topic with our students and I hope you can be a bit more patient with us as we try and complete each project to the best of our abilities.
Best,
365 Eli
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