Computational Linear Algebra
About the Computational Linear Algebra category
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python code for Video 2 lectures
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Any suggestions for understanding orthonormality, orthogonality?
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What is pool8?
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Summarizing the Essence of linear algebra Video series
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Back Propagation Math Simplified
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Custom dot product
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SVD Sign Ambiguity (for PCA "determinism")
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Here's all the Matrix Calculus You Need For Deep Learning
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Timeline for Videos
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[Video 4] What do the diagonals on the graphs of L1 and L2 norms represent?
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My take on what I got from Videos and how I am managing my study
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[Video 2] "MemoryError:" when doing the "Confirm that U, Vh are orthonormal" exercise
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How much about the implementation of randomized SVD implementation in Notebook 2 should have been understood when Rachael moves on to Notebook 3?
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Video 4 - How does taking powers of A help us get a better approximation?
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Any suggestions for brushing up on Calculus?
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Are all matrix decomposition slow or is it just SVD?
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Minimizing forbenius norm is basically trying to make all elements of matrix as small as possible
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What does the plot of components represent in video 2/notebook 2?
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CNN and back propagation
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[Video 3] [Discussion] I think that in TF-IDF SVD negative values should be representing abstract concepts rather than the words themselves
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Compressed Sensing
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Comp Lin Alg Blog
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Video 1 questions and feedback
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Notebook 2 - In most cases we won't be able to reconstruct the matrices exactly - why?
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My take on why we I am doing this course what I achieved at the end of Lesson 1
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A way to have the timing run just once and then run it throughout the notebook
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3. Background Removal with Robust PCA --- Attribute error in video.subclip(0,50).ipython_display(width=300)
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[Homework 1] - Question 6 (Orthogonal Matrix Proof)
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Part 3 – Background Removal with Robust PCA
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