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Machine Learning Basics
  • Level Foundation
  • المدة 15 ساعات hours
  • الطبع بواسطة Sungkyunkwan University
  • Offered by

عن

In this course, you will: a) understand the basic concepts of machine learning. b) understand a typical memory-based method, the K nearest neighbor method. c) understand linear regression. d) 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.

الوحدات

What is machine learning

    • 1 Videos
    • 1 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Quiz 1

1 Videos

  • Let’s talk about machine learning

1 Readings

  • A to Z of AI/Machine Learning 1

Three types of machine learning

    • 1 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Quiz 2

1 Videos

  • Supervised Learning, Unsupervised Learning, Reinforcement Learning

1 Readings

  • A to Z of AI/Machine Learning 2

Model Analysis

    • 1 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Quiz 3

1 Videos

  • Overfitting vs. Generalization, model evaluation

1 Readings

  • A to Z of AI/Machine Learning 3

The basic concpet of kNN

    • 1 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Quiz 1

1 Videos

  • How k-NN works

1 Readings

  • kNN introduction

Variation of k-NN

    • 1 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Quiz 2

1 Videos

  • Weight factors, kernels for the k-NN

1 Readings

  • kNN curse of Dimensionality

Examples with kNN

    • 1 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Quiz 3

1 Videos

  • k-NN Classification implementations

1 Readings

  • kNN Distance measures

Linear regression I

    • 1 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Quiz 1

1 Videos

  • Problem definition and solution in LR

1 Readings

  • Simple linear regression

Linear regression II

    • 1 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Quiz 2

1 Videos

  • Additive Linear model

1 Readings

  • Tests and intervals

Linear regression III

    • 1 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Quiz 3

1 Videos

  • Implementation of linear regression

1 Readings

  • Multiple Linear Regression

Logistic regression I

    • 1 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Quiz 1

1 Videos

  • What is a good model?

1 Readings

  • The Logit and Logistic Transformations

Logistic regression II

    • 1 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Quiz 2

1 Videos

  • Logistic regression as a Linear classifier

1 Readings

  • Residual Diagnostics Report

Logistic regression III

    • 1 Videos
    • 1 Readings
    • 2 Assignment
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2 Assignment

  • Quiz 3
  • Final Test

1 Videos

  • Implementation of logistic regression

1 Readings

  • Example 2 – Subset Selection

Auto Summary

Discover the fundamentals of machine learning with Coursera's "Machine Learning Basics." Ideal for beginners in IT & Computer Science, this foundational course covers key concepts like K nearest neighbor, linear regression, and model analysis. With a 900-minute duration, it requires basic Python programming and math skills. Available with Starter and Professional subscriptions, it's perfect for those eager to dive into machine learning.

Jaekwang KIM
Instructor

Jaekwang KIM