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Matrices and graphs
The single most undervalued fact of linear algebra: matrices are graphs, and graphs are matrices
Jan 9, 2023
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Tivadar Danka
378
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Matrices and graphs
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25
The Camel Principle
What it is, how it works, and why it is essential
May 5
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Tivadar Danka
151
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The Camel Principle
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24
Vectorization in theory
Making expressions do more, faster
May 1, 2024
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Tivadar Danka
66
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Vectorization in theory
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5
Machine Learning From Zero is ready to go!
The open source neural-networks-from-scratch book you were all waiting for
Oct 13, 2024
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Tivadar Danka
57
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Machine Learning From Zero is ready to go!
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5
Can Large Language Models replace mathematicians?
Exploring the mathematical thinking of humans and LLMs
Apr 27
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Tivadar Danka
51
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Can Large Language Models replace mathematicians?
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8
Introduction to Computational Graphs
Neural Networks From Scratch, Part I
May 14
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Tivadar Danka
39
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Introduction to Computational Graphs
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4
How large that number in the Law of Large Numbers is?
All large numbers are large, but some are larger than others
Sep 4, 2023
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Tivadar Danka
and
Levi
41
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How large that number in the Law of Large Numbers is?
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The Derivatives of Computational Graphs
Forward-mode differentiation and its shortcomings
May 30
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Tivadar Danka
37
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The Derivatives of Computational Graphs
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How to grow a decision tree
Beating neural networks one if-else condition at a time
Oct 26, 2024
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Tivadar Danka
35
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How to grow a decision tree
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4
The Computer Scientist's Guide to Graph Theory, ep. 03
Eulerian and Hamiltonian tours
Jan 8, 2024
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Tivadar Danka
and
Alejandro Piad Morffis
39
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The Computer Scientist's Guide to Graph Theory, ep. 03
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The Maximum Likelihood Estimation
(is the foundation of machine learning)
Jan 2, 2024
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Tivadar Danka
37
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The Maximum Likelihood Estimation
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Vectorization in practice
Making data structures do less, faster
May 14, 2024
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Tivadar Danka
37
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Vectorization in practice
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