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Machine Learning From Scratch in Python - Full Course With 12 Algorithms

Python Engineer via YouTube

Overview

Prepare for a new career with $100 off Coursera Plus
Gear up for jobs in high-demand fields: data analytics, digital marketing, and more.
Learn to implement popular Machine Learning algorithms from scratch using Python and NumPy. The course covers algorithms such as KNN, Linear Regression, Logistic Regression, Naive Bayes, Perceptron, SVM, Decision Tree, Random Forest, PCA, K-Means, AdaBoost, and LDA. The goal is to help students write cleaner code and understand the inner workings of these algorithms. The course is suitable for individuals interested in Machine Learning and Python programming.

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

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