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Machine Learning That Even My Mom Can Do (Basic Theory)

The first step in learning AI: We've created the perfect curriculum for AI beginners! The first step: getting familiar with AI foundational theory! Learn basic machine learning concepts with various examples and take quizzes to review the theory!

(4.9) 14 reviews

123 learners

  • yc
개념정리
머신러닝기초
이론 중심
Machine Learning(ML)
Scikit-Learn

Reviews from Early Learners

What you will gain after the course

  • ⭐ What is Machine Learning?

  • ⭐ Understanding the operational principles and evaluation metrics of classification, regression, clustering, and recommendation system models

  • ⭐ Completely master the fundamental theories with diverse examples and animation!

  • ⭐ Check what you've learned with a pop quiz!

📢 This lecture is for non-majors.

Artificial intelligence, solved very easily!

I have excluded statistical and mathematical concepts as much as possible!

Theory lectures, don't be afraid!

Machine Learning That Even Our Mom Can Do (Basic Theory)

Artificial Intelligence (AI)

Machine Learning

Scikit-Learn

Course Introduction

  • Theory is the stepping stone for various code applications.

  • As a non-major, I won the grand prize and excellence award in contests, the first prize in competitions, and the grand prize and excellence award for projects in just 5 months .

  • You need to know the principles to be able to apply them to various situations and data.

  • When learning about artificial intelligence for the first time, various terms are thrown around, and the learning order felt unfamiliar while learning according to the curriculum at the institution . We thought a lot about it and modified and arranged the order so that even beginners can follow along with as little inconvenience as possible .

  • Rather than simply explaining mathematical and statistical concepts, when related references are made to models or indicators, the necessity of the corresponding formula or concept is mentioned, making it much easier to understand and convince, making learning smoother.

Lecture outline

  • We use only the minimum mathematical and statistical concepts necessary for understanding, and even then, we have organized them all into examples for easy understanding.

  • By using various visual aids and animations, we have minimized unnecessary lines of text in the material to make it less boring even though it is a theoretical lecture.


  • Those who do not know about machine learning will be able to learn systematically and broadly without feeling burdened, and those who know about machine learning will be able to establish the concept accurately once again.

  • This is a basic course that covers almost all parts of machine learning that can be intuitively understood, and concepts such as SVM, ROC-AUC, and dimensionality reduction natural language processing (NLP) are covered in the advanced machine learning theory.

  • Since all lectures focus on future deep learning lectures, we recommend this course to those who want to build a solid foundation from machine learning .

Lecture Features

🎯 This course consists of only theory lectures without any code practice.

🎯 Animation material provided

🎯 Theory note test provided for review

Step-by-step learning content

This course is the first of five curricula. The remaining curricula will be released sequentially.

Lecture Preview

Some animated material on Similarity Search. (No audio description)

Mean-Shift clustering among the three clustering methods

One of the slides.

Among the four recommendation systems, content-based filtering

One of the slides.

One of the example slides explaining the CART model.

One of the slides on model validation and evaluation metrics.

Part 2 of the animation on the differences between simple linear regression models and multiple linear regression models. (No audio explanation)

Understand what you've learned through code, without coding.

Understanding gradient descent in a step-by-step approach.

Recommended for
these people

Who is this course right for?

  • ⭐ AI Basics

  • ⭐ People who want to study artificial intelligence but don't know where to start

  • ⭐ People who have difficulty completing lectures due to high barriers to entry caused by formulas and complex terminology

  • ⭐ People who want to study with a systematic curriculum

  • ⭐ Those who want to take machine learning concept and theory lectures

Need to know before starting?

  • (No prior knowledge of Python or data tools is required for the theory lectures.)

Hello
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196

Learners

17

Reviews

5

Answers

4.9

Rating

3

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Curriculum

All

22 lectures ∙ (4hr 11min)

Published: 
Last updated: 

Reviews

All

14 reviews

4.9

14 reviews

  • penguinhing님의 프로필 이미지
    penguinhing

    Reviews 12

    Average Rating 4.1

    Edited

    5

    27% enrolled

    Is the instructor's mother a Seoul National University professor?

    • yc
      Instructor

      My mother has always been someone who works hard.. There's nothing that can't be achieved if you put in the effort!!🥹

    • 😊😊 Just kidding! Thank you for providing the lectures!

  • kfqsangwoo9149님의 프로필 이미지
    kfqsangwoo9149

    Reviews 1

    Average Rating 5.0

    5

    18% enrolled

    I was going crazy not knowing what I was even coding, but I feel so relieved now. When will the deep learning lectures be uploaded??? Please make them quickly 😊😊

    • yc
      Instructor

      Thank you for the positive feedback! We are planning a deep learning course as well, so please stay tuned 🔥

  • sohyun5051님의 프로필 이미지
    sohyun5051

    Reviews 2

    Average Rating 5.0

    5

    55% enrolled

    I thought "machine learning" would be difficult, but after listening to the theory lecture, I immediately understood what kind of technology it is and how it works. The lecture explained the overall structure in a way that it stayed in my head, and clearly explained how each concept differs. I'm excited for the practical training now that I understand machine learning!

    • yc
      Instructor

      Thank you for the positive feedback! Solidifying the theory with practical exercises in that section will help you gain a deeper understanding. Keep up the great work until the end of the course! 🔥

  • gksmfqlc0750님의 프로필 이미지
    gksmfqlc0750

    Reviews 4

    Average Rating 4.8

    Edited

    5

    100% enrolled

    Please teach in an easy-to-understand manner, just like the lecture title! There's even a pop quiz after each chapter, which helps me remember things better. Above all, I had a vague understanding of machine learning theory and concepts, but the terminology and the need to look up data every time didn't resonate with me, so it didn't stick in my head. But through this lecture, I'm understanding things I couldn't before, and seeing things I couldn't see...it's amazing. Thank you 😢😢😢 I'm willing to take advanced theory and practical training courses as soon as they come out!!

    • yc
      Instructor

      Thank you for the great review! If you review the theory thoroughly and then take the practical lessons, you'll see things you didn't see before in the practical sessions as well! Keep up the good work! 🔥

  • gazxxni님의 프로필 이미지
    gazxxni

    Reviews 3

    Average Rating 5.0

    5

    32% enrolled

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