Embark on a comprehensive 5-hour video course that delves into implementing 12 popular Machine Learning algorithms from scratch using Python and NumPy. Learn to code KNN, Linear Regression, Logistic Regression, Naive Bayes, Perceptron, SVM, Decision Trees, Random Forest, PCA, K-Means, AdaBoost, and LDA. Gain hands-on experience with each algorithm through step-by-step implementations, including data loading from CSV files. Access accompanying code on GitHub and join a supportive Discord community to enhance your learning experience. Perfect for those seeking to deepen their understanding of Machine Learning fundamentals and improve their Python programming skills.
Machine Learning From Scratch in Python - Full Course With 12 Algorithms
Overview
Syllabus
​ - Introduction
​ - 1 KNN
​ - 2 Linear Regression
​ - 3 Logistic Regression
​ - 4 Regression Refactoring
​ - 5 Naive Bayes
​ - 6 Perceptron
​ - 7 SVM
​ - 8 Decision Tree Part 1
​ - 9 Decision Tree Part 2
​ - 10 Random Forest
​ - 11 PCA
​ - 12 K-Means
​ - 13 AdaBoost
​ - 14 LDA
​ - 15 Load Data From CSV
Taught by
Python Engineer
