Linear Algebra - Math for Machine Learning
Learners:
Instructor: Weights & Biases
Duration: 1.00
Linear Algebra is an important tool for Machine Learning, as it allows for the representation of linear functions using arrays. This course provides an introduction to the fundamentals of linear algebra, and how it can be used to optimize functions. It also covers the concept of refactoring, which is the process of restructuring code for improved performance.▼
Course Feature
Cost:
Free
Provider:
Youtube
Certificate:
Paid Certification
Language:
English
Start Date:
On-Demand
Course Overview
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Updated in [February 21st, 2023]
Linear Algebra - Math for Machine Learning is a course designed to help learners understand the fundamentals of linear algebra and its application in machine learning. It covers topics such as why linear algebra is important, the differences between linear algebra and algebra, how arrays can be used to represent linear functions, the concept of refactoring, and the use of the Singular Value Decomposition (SVD) in machine learning. Learners will gain an understanding of the fundamentals of linear algebra and its application in machine learning, as well as the ability to apply linear algebra to solve problems in machine learning. Additionally, learners will gain an understanding of the importance of refactoring and the use of the SVD in machine learning. Finally, learners will be provided with a review of the takeaways and additional resources to further their learning.
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