Positive Definite Matrices vs Positive Semidefinite Matrices

Developers should learn about positive definite matrices when working on optimization problems (e meets developers should learn about positive semidefinite matrices when working in machine learning (e. Here's our take.

Positive Definite Matrices

Nice Pick

Developers should learn about positive definite matrices when working on optimization problems (e

Pros

• g
• Related to: linear-algebra, matrix-decomposition

Cons

• Specific tradeoffs depend on your use case

Positive Semidefinite Matrices

Developers should learn about positive semidefinite matrices when working in machine learning (e

Pros

• g
• Related to: linear-algebra, convex-optimization

Cons

• Specific tradeoffs depend on your use case

The Verdict

Use Positive Definite Matrices if: You want g and can live with specific tradeoffs depend on your use case.

Use Positive Semidefinite Matrices if: You prioritize g over what Positive Definite Matrices offers.

The Bottom Line

Positive Definite Matrices wins

Developers should learn about positive definite matrices when working on optimization problems (e