If machine studying is a automobile, then linear algebra is the engine. It powers:
- Mannequin coaching (particularly in deep studying)
- Function transformations
- Similarity computations
- Optimization algorithms
From calculating a buyer’s similarity rating to processing huge SAP gross sales matrices or Buyer 360 consumer profiles — each ML operation entails vectors, matrices, and linear transformations.
On this article, we’ll:
- Construct an intuitive understanding of linear algebra
- Find out how vectors and matrices gas ML
- Stroll by means of real-world enterprise use instances utilizing Databricks
Linear algebra is the department of arithmetic that offers with vectors, matrices, and linear transformations.
In machine studying, it helps you:
- Symbolize information and options
- Remodel inputs into outputs (by way of fashions)
- Carry out environment friendly matrix operations that scale to huge information
Let’s break it down with ideas and examples.
