Linear Algebra Leading to Machine Learning/Deep Learning

Covers essential linear algebra for Machine Learning/Deep Learning research.

(4.5) 수강평 44개

강의소개.상단개요.수강생.short

난이도 입문

수강기한 무제한

Linear Algebra
Linear Algebra
Machine Learning(ML)
Machine Learning(ML)
Deep Learning(DL)
Deep Learning(DL)
Linear Algebra
Linear Algebra
Machine Learning(ML)
Machine Learning(ML)
Deep Learning(DL)
Deep Learning(DL)

먼저 경험한 수강생들의 후기

먼저 경험한 수강생들의 후기

4.5

5.0

Chansu Shin

67% 수강 후 작성

I'm listening. Please explain it so I can understand.

5.0

산보행

100% 수강 후 작성

I just learned linear algebra for the first time and it seems to be well organized.

5.0

한밭구장

100% 수강 후 작성

Thank you for the great lecture. I hope it will be helpful to everyone.

강의상세_배울수있는것_타이틀

  • Mathematics required for Machine Learning/Deep Learning

  • The Relationship Between Linear Algebra and Machine Learning

  • Essential mathematical expressions

Leading to machine learning/deep learning
Learn linear algebra and machine learning together 📖

Hello, I am Deep Learning Ho-hyung, who currently runs a YouTube channel related to deep learning/machine learning .
Based on knowledge of mathematics/data analysis, experience with numerous deep learning/machine learning projects, and experience as a research engineer
We will point out the contents that you absolutely must study.

Knowledge of mathematics and machine learning/deep learning
Are you still separated?

artificial neural network
Manufacturing, autonomous vehicles, healthcare, biotechnology, robotics, etc.
It is a powerful artificial intelligence technology that is being applied in a wide range of fields.

In fact, the number of submitted papers is increasing every year, and many universities around the world, including Korea, are establishing AI-related departments, and the industry is investing heavily in them. This course is a mathematics course designed to help you study deep learning/machine learning in line with this trend.



This course covers the linear algebra required for studying deep learning/machine learning/data analysis .
Have you ever thought about whether you should study "math" while studying artificial intelligence or data analysis?
Or have you ever struggled to understand machine learning algorithms due to a lack of basic math skills?
As a math/data analysis major, I 'll tell you 'where' and 'why' math is used.


What you will learn in this course ✏️

Are you still just using libraries without understanding the algorithms?
Model optimization and tuning require mathematical understanding.
In this lecture , we will discuss the basics of linear algebra and machine learning.


We'll answer your questions in advance 🙋🏻‍♂️

Q. Can non-majors also take the course?

Yes, of course. You can take this course regardless of your major!

Q. What are the benefits of learning linear algebra?

All data is converted into matrix form and operations are performed on it.
Therefore, if you know the linear algebra that can handle matrices, it will ultimately be easy to process data.

Q. Are there any special advantages to this course?

As a former mathematics/data analysis major, I've designed these lectures to convey essential concepts in a simple and concise manner, making them accessible even to those who struggle with math. Furthermore, rather than focusing on mathematical proofs, you'll learn how mathematics is used in real-world data analysis and artificial intelligence, developing a comprehensive understanding.
If you're interested in getting started with deep learning, check out our lecture on understanding deep learning concepts leading to practical artificial intelligence .


Recommended Roadmap 🚩

▲ [Introductory to Beginner] Quick and Reliable Introduction to Deep Learning (Click)

강의소개.콘텐츠.추천문구

학습 대상은 누구일까요?

  • For those new to Machine Learning, Deep Learning

  • Those lacking math basics

  • Curious about Linear Algebra's use in ML/DL?

선수 지식, 필요할까요?

  • Passion to do

강의소개.지공자소개

5,134

수강생

404

수강평

261

답변

4.7

강의 평점

7

강의_other

Hello.

I am Deep Learning Ho-hyung, and I run a YouTube channel related to deep learning and machine learning.

I majored in mathematics and data analysis, and I have completed and am currently working on numerous deep learning projects.

I am Deep Learning Ho-hyung, and I run a YouTube channel focused on deep learning and machine learning. I majored in mathematics and data analysis, and I have completed and am currently working on numerous deep learning projects.

I have knowledge that I can share with you regarding Artificial Intelligence topics such as machine learning, advanced machine learning, deep learning, optimization theory, and reinforcement learning, as well as mathematical subjects including linear algebra, calculus, probability and statistics, analysis, and numerical analysis.

Nice to meet you all! * Related Experience: Current) Numerous SCI(E) papers and international conference presentations Current) Multiple university advisory roles related to AI Former) Senior Researcher at K-Corp - Data Analysis and

Nice to meet you all!

* Relevant Experience Current) Numerous SCI(E) papers and international conference presentations Current) Multiple university advisory roles related to Artificial Intelligence Former) Senior Researcher at K-Corporation - Data Analysis and Simulation: New Product Development

* Related Experience

Current) Numerous SCI(E) papers and presentations at international conferences

Current) Multiple university advisory roles related to Artificial Intelligence

Former Senior Researcher at K-Company - Data Analysis and Simulation: New Product Development, Performance Improvement, and New Technology Application

Author of "Introduction to PyTorch for Deep Learning" (Selected as a 2022 Sejong Book in the Academic Category)

- Data Analysis and Simulation: New product development, performance enhancement, and application of new technologies. Author of "Introduction to PyTorch for Deep Learning" (Selected as a 2022 Sejong Book in the Academic Category).

- Data Analysis and Simulation: New product development, performance enhancement, and application of new technologies. Author of "Introduction to PyTorch for Deep Learning" (Selected as a 2022 Sejong Book in the Academic Category).

- Data Analysis and Simulation: New product development, performance enhancement, and application of new technologies. Author of "Introduction to PyTorch for Deep Learning" (Selected as a 2022 Sejong Book in the Academic Category).

- Data Analysis and Simulation: New product development, performance enhancement, and application of new technologies. Author of "Introduction to PyTorch for Deep Learning" (Selected as a 2022 Sejong Book in the Academic Category).

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4.5

44개의 수강평

  • son917473086007님의 프로필 이미지
    son917473086007

    수강평 1

    평균 평점 5.0

    5

    100% 수강 후 작성

    I just learned linear algebra for the first time and it seems to be well organized.

    • dlbro
      지식공유자

      Thank you!! Good luck :)

  • templar님의 프로필 이미지
    templar

    수강평 7

    평균 평점 5.0

    5

    100% 수강 후 작성

    Thank you for the great lecture. I hope it will be helpful to everyone.

    • dlbro
      지식공유자

      thank you!!

  • yepsilondelta님의 프로필 이미지
    yepsilondelta

    수강평 17

    평균 평점 4.9

    4

    100% 수강 후 작성

    I think the explanation is too fast for beginners and basic concepts are omitted.

    • dlbro
      지식공유자

      To avoid getting bored, I edited out even the breathing sounds to create a video without dragging out the class. If you felt that the lecture was going too fast, I recommend that you adjust the speed to listen to the lecture. If you have any questions, please leave them in the question section :) Thank you for your review!

  • hyunahn23님의 프로필 이미지
    hyunahn23

    수강평 2

    평균 평점 5.0

    5

    100% 수강 후 작성

    • devshin91님의 프로필 이미지
      devshin91

      수강평 5

      평균 평점 5.0

      5

      67% 수강 후 작성

      I'm listening. Please explain it so I can understand.

      • dlbro
        지식공유자

        Thank you for your course review :) Study hard!!

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