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Introduction to Machine Learning
In this course, we will cover how to implement basic supervised learning and unsupervised learning algorithms.
19 Lessons
15 Challenges
With Certificate
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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