Computational Linear Algebra
About the Computational Linear Algebra category
(6)
Here's all the Matrix Calculus You Need For Deep Learning
(2)
Timeline for Videos
(2)
[Video 4] What do the diagonals on the graphs of L1 and L2 norms represent?
(9)
My take on what I got from Videos and how I am managing my study
(5)
[Video 2] "MemoryError:" when doing the "Confirm that U, Vh are orthonormal" exercise
(2)
How much about the implementation of randomized SVD implementation in Notebook 2 should have been understood when Rachael moves on to Notebook 3?
(1)
Video 4 - How does taking powers of A help us get a better approximation?
(1)
Any suggestions for understanding orthonormality, orthogonality?
(4)
Any suggestions for brushing up on Calculus?
(14)
Are all matrix decomposition slow or is it just SVD?
(2)
Minimizing forbenius norm is basically trying to make all elements of matrix as small as possible
(2)
What does the plot of components represent in video 2/notebook 2?
(2)
CNN and back propagation
(3)
[Video 3] [Discussion] I think that in TF-IDF SVD negative values should be representing abstract concepts rather than the words themselves
(1)
Compressed Sensing
(2)
Comp Lin Alg Blog
(2)
Video 1 questions and feedback
(2)
Notebook 2 - In most cases we won't be able to reconstruct the matrices exactly - why?
(4)
My take on why we I am doing this course what I achieved at the end of Lesson 1
(1)
A way to have the timing run just once and then run it throughout the notebook
(1)
3. Background Removal with Robust PCA --- Attribute error in video.subclip(0,50).ipython_display(width=300)
(1)
[Homework 1] - Question 6 (Orthogonal Matrix Proof)
(2)
Part 3 – Background Removal with Robust PCA
(7)
Packages and Extensions for Jupyter Notebooks
(3)
Pre requisites Video 8 - Some squishes feel squishier
(2)
Regarding pre requisites
(4)
Does this use Anaconda 2 or 3?
(5)
next page →