Logistic Regression and the Perceptron Algorithm: A friendly introduction @SerranoAcademy

Uploaded January 2019 | Updated September 2026, 2 weeks ago

For a code implementation, check out these repos:
github.com/luisguiserrano/manning/tree/master/Chapter_5_Perceptron_Algorithm
github.com/luisguiserrano/manning/tree/master/Chapter_6_Logistic_Regression

Announcement: New Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML
40% discount code: serranoyt

An introduction to logistic regression and the perceptron algorithm that requires very little math (no calculus or linear algebra), only a visual mind.

0:00 Introduction
0:08 Series of 3 videos
0:41 E-mail spam classifier
7:19 Classification goal: split data
11:36 How to move a line
12:21 Rotating and translating
18:47 Perceptron Trick
23:20 Correctly and incorrectly classified points
24:20 Positive and negative regions
27:18 Perceptron Error
29:40 Gradient Descent
34:36 A friendly introduction to deep learning and neural networks
37:48 Activation function (sigmoid)
38:31 Log-Loss Error
41:37 Perceptron Algorithm
42:45 Logistic regression algorithm
44:48 Thank you!

Logistic Regression and the Perceptron Algorithm: A friendly introduction

Direct Preference Optimization (DPO) - How to fine-tune LLMs directly without reinforcement learning

A friendly introduction to Bayes Theorem and Hidden Markov Models

Kolmogorov-Arnold Networks (KANs) - What are they and how do they work?

Mean, Variance, Skewness, and Kurtosis - Math for ML with Deeplearning.ai

Why is ChatGPT so bad at telling jokes (yet so good at writing poems?)

Thompson sampling, one armed bandits, and the Beta distribution

How do you minimize a function when you cant take derivatives? CMA-ES and PSO

Eulers number, derivatives, and the bank at the end of the universe