Linear Algebra for Machine Learning
Learn the essential mathematics for Data Science and machine learning. Grasp the Linear algebra intuition essential for ML algorithms. Implement these ideas in code, not just on pen and paper.
- Grasp the Linear algebra intuition essential for ML algorithms.
- Implement these ideas in code, not just on pen and paper.
Prabhakaran SPrincipal Data Scientist
Included in All-Access, one membership for every course.
- Lessons
- 20, in 4 chapters
- Video
- 1 h 49 min
- Free to watch
- 1 lesson
- Certificate
- On completion
What you'll be able to do
- Mathematical intuition required for DS and ML
- Dot prod, inner prod, outer prod, matrix multiplication
- Vectors, matrices, and higher-dimensional tensors
- Matrix inverse, transpose, determinant, trace
- Eigenvalues and Eigenvectors
- Eigen Decomposition, SVD and PCA
- Applying linear algebra in Python
Course content
4 chapters · 20 lessons · 1 h 49 min · 1 free to preview
01Introduction10 lessons · 39 min
- Why Learn Linear Algebra?Preview2:30
- Download Resources1:00
- Types of Tensors4:25
- Scalars6:03
- Vectors6:02
- L1 and L2 Norm5:17
- Angle between Vectors3:27
- Projections and Unit Vector2:49
- Basis, Orthogoanal and Orthonormal Vectors6:44
- Course Review1:00
02Matarices3 lessons · 22 min
- Types of Matrices2:33
- Matrix Operations15:08
- Orthogonal and Orthonormal Matrices4:45
03Essential Equations3 lessons · 11 min
- Equation of line, plane and hyperplane4:17
- Geometric interpretation of Weights vector2:34
- Equation of Circle, Sphere and Hyperplane3:39
04Towards SVD and PCA4 lessons · 38 min
- Eigenvalues and Eigenvectors6:43
- Eigen Decomposition2:39
- Singular Value Decomposition (SVD)7:17
- Principal Component Analysis (PCA)21:50
What you need
- Basics of Python
- Foundational knowledge of Data Science
- High school maths
Who this course is for
- Data Science Aspirants
- Data Science Professionals
- Software/Data engineers interested in quantitative analysis
- Professionals working with large datasets
- Data analysts, economists, researchers
Your instructor
Prabhakaran S
Principal Data Scientist
My name is Selva, and I am super excited to mentor you on this course!
I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I've deployed 20+ global products. I'm also the Founder and Chief Author of Machine Learning Plus, which has over 4M annual readers.
I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, I've put up the series of courses and projects with detailed explanations, just like on-the-job experience. Hope you love it!
- from 3,965 ratings
- 4.92
- learners
- 57K+
- courses
- 85
Questions
How do I get this course?
It is part of All-Access: one membership that opens all 85 courses. The plans and prices are on our course site. You can watch the free preview lessons before you join.
Can I get a refund?
Yes. If the membership is not right for you, ask for a refund within 30 days of your first payment.
Can I learn on my phone?
Yes. Lessons play in the browser on any phone, tablet or computer, and your place is saved for the next device.
I am already a member. Where are my courses?
On our course site, edu.machinelearningplus.com. Sign in there with the email you joined with. The courses move to this site later, with your access, and you will not pay again.
