Mathematics for AI and Machine Learning

Foundations for modern AI and machine learning

Upper Triangular Matrix

Chapter 2 Mathematics for AI

Chapter 2: Matrix — Upper triangular (also appears in Ch. 5)

High-resolution PNG
Upper Triangular Matrix — high-resolution mind-map icon

From the book

Chapter 2: Matrix. In the chapter mind map this icon labels Upper triangular. The discussion below is excerpted and lightly edited from § Theorem: Upper Bound on Rank in Mathematics for AI and Machine Learning. Related material also appears in Chapter 5 (Solving Linear Systems via Forward/Backward Substitution).

Each column lies in $\mathbb{R}^M$, so the column span has dimension at most $M$. There are $N$ columns, so the span dimension is at most $N$. Hence,

What this drawing shows

What you see. Matrix with nonzero entries on and above the main diagonal, used in back substitution and QR factors.

In the mind map. Chapter 2 — Upper triangular. See From the book above for definitions, figures, and worked examples.

Also appears in Ch. 5 (Solving Linear Systems via Forward/Backward Substitution).

Where to read next

Open Chapter 2 companion →

Read the full definitions, figures, and worked examples in Chapter 2: Matrix — see the mind-map node Upper triangular.

This concept is also referenced in Chapter 5 (Solving Linear Systems via Forward/Backward Substitution).