Date of Award

Spring 6-14-2025

Document Type

Undergraduate Thesis

Degree Name

B.S. in Mathematics

Organizational Unit

College of Natural Science and Mathematics, Mathematics

First Advisor

Alvaro Arias

Copyright Statement / License for Reuse

All Rights Reserved
All Rights Reserved.

Keywords

Machine learning, Artificial neural network, Rectified linear unit

Abstract

At its core, learning is an algorithmic process: it begins with input data, undergoes a series of transformations or computations, and yields an output intended to solve a specific task. This output is then compared against a target or desired result, and the internal mechanisms are updated based on how well the output aligns with expectations. While this feedback-driven process occurs almost effortlessly in humans, it is a far more structured, deliberate, and computationally intensive undertaking for machines.

Copyright Date

6-19-2025

Publication Statement

Copyright is held by the author. User is responsible for all copyright compliance.

Rights Holder

Aidan Redmond Brownell

Provenance

Received from author

File Format

application/pdf

Language

English (eng)

Extent

24 pgs

File Size

684 KB



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