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1. The Most Important Machine Learning Equations: A Comprehensive Guide

   A comprehensive guide covering the most critical machine learning equations, including probability, linear algebra, optimization, and advanced concepts, with Python implementations.

   2025-09-14 Tags: machine learning, equations, probability, linear algebra, optimization, deep learning, python, bayes theorem, entropy, gradient descent, softmax, attention mechanism by klotz
2. Derivatives, Gradients, Jacobians and Hessians – Oh My!

   This article explains how derivatives, gradients, Jacobians, and Hessians fit together and shows examples of what they are used for, including optimization and rendering.

   2025-08-17 Tags: derivatives, gradients, jacobians, hessians, calculus, optimization, gradient descent, rendering, machine learning by klotz
3. What We Still Don’t Understand About Machine Learning

   This article explores some of the mysteries and unsolved phenomena in machine learning, focusing on concepts like Batch Normalization, overparameterized models, and the implicit regularization effects of gradient descent.

   2024-07-27 Tags: machine learning, deep learning, batch normalization, gradient descent, neural networks by klotz
4. An Introduction to Gradient Descent and Linear Regression

   2018-09-19 Tags: introduction, tutorial, gradient descent, linear regression, machine learning, statistics by klotz
5. Coding Deep Learning for Beginners — Linear Regression (Part 3): Training with Gradient Descent

   2018-08-24 Tags: deep learning, tutorial, gradient descent by klotz
6. Intro to optimization in deep learning: Gradient Descent

   2018-06-02 Tags: deep learning, gradient descent by klotz

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