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Introduction to Machine Learning
In this course, we will cover how to implement basic supervised learning and unsupervised learning algorithms.
Prerequisites
Knowledge in Python, NumPy & Pandas
Save for laterThe Beginning of ML Journey
ML Introduction
Data to feed a model
What is a ML model
Machine Learning Overview
Supervised learning
Unsupervised learning
K-Nearest-Neighbors (KNN)
KNN Introduction
fit method
predict method
K-Means Algorithm
K-Means Introduction
fit method
predict method
Naive Bayes
Naive Bayes Introduction
fit method
predict method
Other Models
Logistic Regression
Linear Regression
Decision Tree
Support Vector Machine (SVM)
Models quiz
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