Linear Algebra
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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.

Created by Selva Prabhakaran

  • 19 Video Lessons

  • English

  • English captions

What you will learn

01

Mathematical intuition required for DS and ML

02

Dot prod, inner prod, outer prod, matrix multiplication

03

Vectors, matrices, and higher-dimensional tensors

04

Matrix inverse, transpose, determinant, trace

05

Eigenvalues and
Eigenvectors

06

Eigen Decomposition, SVD and PCA

07

Applying linear algebra in Python

Course Curriculum

Requirements

  • Courses Page1 Basics of Python
  • Courses Page1 Foundational knowledge of Data Science
  • Courses Page1 High school maths

Who should attend this course?

  • Data Science Aspirants

  • Data Science Professionals

  • Software/Data engineers interested in quantitative analysis

  • Professionals working with large datasets

  • Data analysts, economists, researchers

Instructor

Selva Prabhakaran Principal Data Scientist

My name is Selva, and I am super excited to mentor you on this project!

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 & 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 an on the job experience. Hope you love it!

  • 4.5+Instructor rating

  • 200+ reviews

  • 75K+students

  • 50+ Courses

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