Lectures related to Linear Similarities and Similitudes

Covers the topology of Riemann surfaces, focusing on orientation and orientability.

Explores the composition of applications in mathematics and the importance of understanding their properties.

Explores mapping functions, surjections, injective and surjective functions, and bijective functions.

Covers the concept of graph sketching with a focus on connected components.

Explores generalization error in machine learning, focusing on data distribution and hypothesis impact.

Covers normed spaces, dual spaces, Banach spaces, Hilbert spaces, weak and strong convergence, reflexive spaces, and the Hahn-Banach theorem.

Explores homotheties and translations in geometry, focusing on preserving alignment and distances.

Explores matrix representations of linear maps and their invariance, using examples and special cases.

Introduces Cartesian product and induction for proofs using integers and sets.