SKKU - Machine Learning Basics
- Offered byCoursera
Machine Learning Basics at Coursera Overview
Duration | 15 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Machine Learning Basics at Coursera Highlights
- Earn a Certificate upon completion
Machine Learning Basics at Coursera Course details
- Understand the basic concepts of machine learning
- Understand a typical memory-based method, the K nearest neighbor method
- Understand linear regression
- Understand model analysis.
- Please make sure that you're comfortable programming in Python and have a basic knowledge of mathematics including matrix multiplications, and conditional probability
Machine Learning Basics at Coursera Curriculum
The basic concepts of machine learning
Let's talk about machine learning
Supervised Learning, Unsupervised Learning, Reinforcement Learning
Overfitting vs. Generalization, model evaluation
A to Z of AI/Machine Learning 1
A to Z of AI/Machine Learning 2
A to Z of AI/Machine Learning 3
Quiz 1
Quiz 2
Quiz 3
The k-Nearest Neighbors
How k-NN works
Weight factors, kernels for the k-NN
k-NN Classification implementations
kNN introduction
kNN curse of Dimensionality
kNN Distance measures
Quiz 1
Quiz 2
Quiz 3
Linear Regression
Problem definition and solution in LR
Additive Linear model
Implementation of linear regression
Simple linear regression
Tests and intervals
Multiple Linear Regression
Quiz 1
Quiz 2
Quiz 3
Logistic Regression
What is a good model?
Logistic regression as a Linear classifier
Implementation of logistic regression
The Logit and Logistic Transformations
Residual Diagnostics Report
Example 2 -Subset Selection
Quiz 1
Quiz 2
Quiz 3
Final Test
Machine Learning Basics at Coursera Admission Process
Important Dates
Other courses offered by Coursera
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