You can find the source on the GitHub project.
The notes are collecting using my interpretation of the Zettelkasten method.
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Convolutional Neural Network (Coursera)
Notes from Coursera's Convolutional Neural Networks by Andrew Ng, Younes Bensouda Mourri and Kian Katanforoosh
Contents

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization (Coursera)
Notes from Coursera's Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization by Andrew Ng, Younes Bensouda Mourri and Kian Katanforoosh
Contents

Structuring Machine Learning Projects (Coursera)
Notes from Coursera's Structuring Machine Learning Projects by Andrew Ng, Younes Bensouda Mourri and Kian Katanforoosh
Contents

Introduction to Recommender Systems: NonPersonalized and ContentBased
Notes from Coursera's Introduction to Recommender Systems: NonPersonalized and ContentBased by Joseph A Konstan and Michael D. Ekstrand.
Contents

Data Structures and Performance
Notes from Coursera's Data Structures and Performance by Christine Alvarao, Leo Porter and Mia Minnes.
Contents


Recursive queries in PostgreSQL
For some data relationships in Postgres (or any other relational database that speaks SQL), recursive queries are near inevitable. Let's say you have some toplevel …

Mean Absolute Difference  L1 Loss
Mean Absolute Difference (MAE) is a function for assessing Regression predictions. It's also as L1 Loss because it takes the L1 Norm of the error …

ML Regression
Notes taken during ML Regression by Coursera.
Linear Algebra Refresher
Matrices and Vectors
 Denoted by
n x m
(n rows, m columns).
Special Matrices
 Square …
 Denoted by