Back to Linear Algebra for Machine Learning and Data Science
Learner Reviews & Feedback for Linear Algebra for Machine Learning and Data Science by DeepLearning.AI
2,266 ratings
About the Course
Newly updated for 2024! Mathematics for Machine Learning and Data Science is a foundational online program created by DeepLearning.AI and taught by Luis Serrano. In machine learning, you apply math concepts through programming. And so, in this specialization, you’ll apply the math concepts you learn using Python programming in hands-on lab exercises. As a learner in this program, you'll need basic to intermediate Python programming skills to be successful.
After completing this course, you will be able to:
• Represent data as vectors and matrices and identify their properties using concepts of singularity, rank, and linear independence, etc.
• Apply common vector and matrix algebra operations like dot product, inverse, and determinants
• Express certain types of matrix operations as linear transformations
• Apply concepts of eigenvalues and eigenvectors to machine learning problems
Many machine learning engineers and data scientists need help with mathematics, and even experienced practitioners can feel held back by a lack of math skills. This Specialization uses innovative pedagogy in mathematics to help you learn quickly and intuitively, with courses that use easy-to-follow visualizations to help you see how the math behind machine learning actually works.
We recommend you have a high school level of mathematics (functions, basic algebra) and familiarity with programming (data structures, loops, functions, conditional statements, debugging). Assignments and labs are written in Python but the course introduces all the machine learning libraries you’ll use.
Top reviews
MS
Aug 26, 2024
While people focus on teaching how to solve problems basically, It is very good to see people speak about maths like science as a concept with good visualization!. Great work guys.
PA
May 27, 2023
Best Visual Explanation, I've got new thinking of the same things which I had learned in the Past. It great Course Thanks for making Such Amazing Content.
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