Polynomial-time approximation scheme

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Interpretation of Taylor's Formula: An Example

Covers the interpretation of Taylor's formula through an example, focusing on developing limited series for sin(x) around a=0.

Complexity Classes: P and NP

Explores complexity classes P and NP, highlighting solvable and verifiable problems, including NP-complete challenges.

Transformer Architectures: Subquadratic Attention Mechanisms

Covers transformer architecture and subquadratic attention mechanisms, focusing on efficient approximations and their applications in machine learning.

Numerical Analysis: Introduction to Computational Methods

Covers the basics of numerical analysis and computational methods using Python, focusing on algorithms and practical applications in mathematics.

Complexity of Algorithms: Quiz + Answers

Covers the time complexity of algorithms and includes a quiz.

Numerical Analysis: Introduction to Interpolation Techniques

Covers the basics of numerical analysis, focusing on interpolation methods and their applications in engineering.

Approximation Algorithms

Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.

Stone-Weierstrass Theorem

Explores the Stone-Weierstrass theorem, proving uniform density of specific function families on compact sets.

Orthogonal Polynomials

Explores L^2 bases and orthogonal polynomials, discussing their properties and applications in polynomial approximation.