L-notation

Related lectures (18)

Page 1 of 2

Covers the rules of derivatives, O-notation, and extrema in the context of theorem 6.5 and examples.

Explores derivatives, O-Notation, extrema, and algorithm complexity in Analysis 1.

Covers the Mean Value Theorem in differential calculus, focusing on critical points and global extrema within intervals.

Covers O-Notation, local extrema, and critical points in functions.

Explores algorithmic complexity, visualization of functions, and algorithm efficiency analysis using Python.

Explores advanced big-O facts for powers, logarithms, factorials, and function combinations.

Explores worst-case complexity in computer science and the importance of real-life complexity in algorithm selection.

Covers optimization algorithms, stable matching, and Big-O notation for algorithm efficiency.

Covers proofs of Big-O using witnesses and rules to analyze algorithm complexity.

Explains Big-O notation for algorithm complexity analysis through polynomial examples and growth rate identification.