Introduction to Machine Learning
In this course, we will cover how to implement basic supervised learning and unsupervised learning algorithms.
Syllabus
6 chapters19 lessons3 projects39 quiz questionsThe Beginning of ML Journey
3 lessons6- 01ML Introduction
- 02Data to feed a model
- 03What is a ML model
Machine Learning Overview
2 lessons6- 01Supervised learning
- 02Unsupervised learning
K-Nearest-Neighbors (KNN)
Project3 lessons3- 01KNN Introduction
- 02fit method
- 03predict method
K-Means Algorithm
Project3 lessons3- 01K-Means Introduction
- 02fit method
- 03predict method
Naive Bayes
Project3 lessons3- 01Naive Bayes Introduction
- 02fit method
- 03predict method
Other Models
5 lessons18- 01Logistic Regression
- 02Linear Regression
- 03Decision Tree
- 04Support Vector Machine (SVM)
- 05Models quiz
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