확률과 통계 기초
조범희 (타블렛깎는노인)
수학 좋아하는 사람 손! 확률과 통계 배우고 싶은 사람 손!
중급이상
확률과 통계, 통계
Linear Algebra with Python - Using NumPy and SciPy
In this course, you will learn how to solve various matrix calculation related problems using Python's SciPy library. Even if you do not know Python or have only a little prior knowledge, you will be able to solve the given problems.
Reviews from Early Learners
What you will learn!
How to solve linear algebra problems using python
Utilizing NumPy and SciPy Libraries
Practical applications of matrix operations and improved computational efficiency
No, is this my story?
🌿 CASE 1 🌿
I finished the Introduction to Linear Algebra course. I've finally mastered it. Throw me any problem and I can solve it flawlessly. But... I need to do the singular value decomposition of a 100 x 100 matrix right now. Seriously... I've mastered linear algebra, but this problem is going to take forever.🌿 CASE 2 🌿
Professor: Approximate this data with a quadratic function by tomorrow.
Student: Okay, I understand. How many data points are there?
Professor: 40,000.
student: ??
Professor: Oh, while we're at it, how about fitting a+b*sinh(x)+c*Log(x) as well? Can we do it quickly?
student: ?????????
🌿 CASE 3 🌿
Now that I'm not in college, I can't use Matlab... It's too expensive... Ha... But how do I solve matrix equations...? I'll have to solve some more in the future, but is there any way to do it?
Let's solve various matrix calculation problems using NumPy and SciPy.
To quickly solve matrix calculation problems, you need to use the NumPy and SciPy libraries in Python. Have you ever wanted to solve matrix equations using a computer? Want to find eigenvalues? Or do you need these functions right away?
In this course, you'll use Python's SciPy library to solve a variety of matrix calculation problems. Even if you don't know Python or have a basic understanding of introductory linear algebra, the content is designed to help you apply the knowledge immediately after taking the course. Don't worry, join us!
Learning Objectives 📜
In this course, you will learn how to solve linear algebra problems on a computer using SciPy and NumPy.
People like this will love hearing this! ✨
- Engineering students and graduate students
- Anyone who needs to find the solution to a matrix equation right away
- For those who want to find eigenvalues and eigenvectors right away
- Anyone who wants to try SVD or needs a solution for the least squares method
- Those who studied Introduction to Linear Algebra
- Anyone interested in learning the SciPy library for Python
Check before taking the class! ✒️
- You can take the course even if you do not have any specialized knowledge of Python.
- Lectures and practical training are conducted simultaneously.
- For those who plan to use the Lapack library in the future, I will explain what Lapack functions are related to the functions used in the course.
- In this lecture, we will not learn numerical analysis theory related to matrix calculations.
Questions to ask before taking the class!
Q. Is it true that matrix equations can be solved on a computer?
A. Of course. It would be stranger if it wasn't solved by computer!
Q. I need to find the eigenvalues of a large matrix right now. How do I do it? I can't solve it manually 😭😭
A. Don't worry. You can get it with just a few lines of Python code. This course is for you.
Q. I have no programming experience... but I want to solve linear algebra problems on a computer!
A. Welcome! It's easy to follow.
Q. I heard Python is slow... Isn't it impractical to learn it?
A. The SciPy functions we'll learn utilize functions written in Fortran (developed over decades!). They offer speed and accuracy that are sufficient for practical use.
Q. Where did you hear that... people usually write the code themselves...?
A. There are linear algebra-related functions that have been developed over decades, not just years. Just knowing how to use them can be a huge help in your life.
Would you like to take this course too?
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Recommended for
these people
Who is this course right for?
For those who want to learn linear algebra concepts through actual coding practice
Anyone who wants to learn linear algebra using Python libraries NumPy and SciPy
Anyone who wants to expand their knowledge of computer science and mathematics by covering practical linear algebra concepts.
6,151
Learners
169
Reviews
387
Answers
4.7
Rating
7
Courses
새로운것을 배우고 가르치는걸 좋아합니다.
인프런을 통해 많은 분들에게 도움이 되면 좋겠습니다.
전문분야 (+좋아하는 분야) 👨🎓
- 전공: 원자력
- 수학: 선형대수학개론, 대학미적분, 벡터미적분학, 응용미분방정식, 응용해석방정식, 확률과 통계, 수치해석
- 컴퓨터 언어: 포트란(MPI, OpenMP 포함), Javascript (nodeJS), C#, C++, Python, Solidity, …
출신학교
- 박사: 카이스트, 원자력 및 양자공학과, 2011 ~ 2016
- 석사: 카이스트, 원자력 및 양자공학과, 2009 ~ 2011
- 학부: 카이스트, 원자력 및 양자공학과, 2005 ~ 2009
- 고등학교: 경기과학고, 2003 ~ 2005
경력
- 2019 ~: 인프런강사
- 2017 ~ 2018: 스탠다드에너지, 연구소장
- 2016 ~ 2017: 스탠다드에너지, 특수연구 총괄
링크
- 블로그: https://blog.naver.com/bumhee34
- 유튜브: https://www.youtube.com/channel/UCsaTZaR2itIeT0eVHPi1_cw
- 이메일 bumhee34@gmail.com
Curriculum
All
29 lectures ∙ (13hr 31min)
Published:
Last updated:
Reviews
All
8 reviews
5.0
8 reviews
Gabriel Woojae LimReviews 2
∙
Average Rating 5.0
5
76% enrolled완료수업 25/29, 수강시간 10h33m 에서 첫 후기 남깁니다. 이런거 잘 안남기는 사람이라 지금 남겨야 미루지 않을것 같습니다. 수강동기 : ML 공부하던 중 Numpy slicing을 정확히 배울 필요가 있었고, 강좌를 둘러보다가 여기서 커버가 될 것 같아 수강했습니다. 후기 : 필요했던 Numpy slicing을 정확히 배울 필요가 있었습니다. 조범희님의 선형대수학 강의를 선수강 하지 않았지만, 따라가는데 문제 없었습니다. 이 강좌를 차분히 따라가면 Scipy의 linalg 함수들의 사용법 충분히 배우게 됩니다. 함수사용법에 대한 설명과 예제의 구성이 꼼꼼하며, 수강생이 '당연히 알겠지' 하고 넘어가는 것 없이 자세히 풀어서 설명해주십니다. 그러기에 앞서 올리신 조범희님의 선형대수학 강의가 듣고 싶어집니다. (인프런 리뉴얼 하면 할인권 풀어주시나 했는데.. 없네요. ㅎㅎ)
- 조범희 (타블렛깎는노인)Instructor
소중한 후기 감사합니다!!ㅎㅎ 교과서나 주어진 커리큘럼이 없이 만든 강좌여서 나름 이런저런 노력을해서 만든 강좌다 보니 개인적으로 애착이 많이 가는 강좌입니다. 강좌를 보시면서 부족하거나, 업데이트 됐으면 하는 부분들이 있다면 언제든지 저에게 메시지나 이메일로 피드백 주시면 최대한 반영하도록 하겠습니다. 제가 생각지도 못한 부분들이 있을 수도 있기에 수강생 여러분의 적극적인 의견이 있으면 강좌가 더 업데이트(!) 되고 수정될 수 있습니다. (지금은 또 다른 수학관련 강좌를 만들고 있습니다. 앞으로도 많은 관심 부탁드릴게요 ㅎㅎ)
- 허민규
Reviews 6
∙
Average Rating 5.0
5
45% enrolled강의 초반부에 기회가 된다면 전설의 언어 Fortran 강좌도 열겠다고 하셨는데, 꼭 열어주세요! Fortran을 사용하는 대학원에 있어서 필요합니다.
- 조범희 (타블렛깎는노인)Instructor
추후에라도 꼭 시간닿는대로 만들도록 노력하겠습니다. 감사합니다!
- 웃지요
Reviews 5
∙
Average Rating 4.6
- 이찬호
Reviews 4
∙
Average Rating 4.8
- pro작곡까
Reviews 6
∙
Average Rating 4.8
$42.90
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