| 000 -LEADER |
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| fixed length control field |
03897nam a22003017a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20260824094131.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
260824b |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9798878584753 [paperback] |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
University of Cebu-Banilad |
| Transcribing agency |
University of Cebu-Banilad |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Adams, Jonathan, |
| Relator term |
author. |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
AI foundations of neural networks / |
| Statement of responsibility, etc |
Jonathan Adams. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc |
USA : |
| Name of publisher, distributor, etc |
Independently published, |
| Date of publication, distribution, etc |
c2024. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
68 pages ; |
| Dimensions |
22.7 cm. |
| 336 ## - CONTENT TYPE |
|---|
| Source |
rdacontent |
| Content type term |
text |
| 337 ## - MEDIA TYPE |
|---|
| Source |
rdamedia |
| Media type term |
unmediated |
| 338 ## - CARRIER TYPE |
|---|
| Source |
rdacarrier |
| Carrier type |
volume |
| 505 ## - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Contents: 1 The neuron, The fundamental unit — 2 Activation functions: Bringing neurons to life — The anatomy of layers — Backpropagation learning from errors — Loss functions measuring performance — Optimization algorithms: The road to convergence — 7 Overfitting and generalization — 8 Advanced architecture. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
"Dive into the fascinating world of artificial intelligence with "AI Foundations of Neural Networks." This comprehensive guide demystifies the complex concepts of neural networks, offering a clear and accessible path to understanding the core principles that fuel modern AI systems. From the basic building blocks of neural networks to advanced architectures, this book is designed to provide a thorough grounding in deep learning for readers at all levels of expertise.<br/><br/>Chapters Overview:<br/><br/>The Neuron - The Fundamental Unit: Explore the basic structure that mimics the human brain's neurons, setting the stage for understanding how neural networks operate.<br/>Activation Functions - Bringing Neurons to Life: Learn about the functions that help neural networks make decisions, allowing them to process information in complex ways.<br/>The Anatomy of Layers: Delve into how layers of neurons work together to process data, forming the backbone of neural network architecture.<br/>Backpropagation - Learning from Errors: Understand the mechanism by which neural networks learn from their mistakes, optimizing their performance over time.<br/>Loss Functions - Measuring Performance: Discover how neural networks evaluate their accuracy and make adjustments to improve their predictions.<br/>Optimization Algorithms - The Road to Convergence: Get to grips with the strategies that guide neural networks towards making more accurate predictions.<br/>Overfitting and Generalization: Learn about the challenges of making models that perform well not just on the data they were trained on but on new, unseen data as well.<br/>Advanced Architectures: Explore the frontier of neural network design, including the latest models that drive progress in AI research.<br/>Why This Book?<br/><br/>"AI Foundations of Neural Networks" stands out as a beacon of knowledge, transforming what might appear as a complex field into a series of comprehensible concepts. With a focus on clarity, practical insights, and intuitive understanding, this book bridges the gap between theoretical knowledge and real-world application. Whether you're a student, professional, or enthusiast eager to navigate the realm of AI, this guide illuminates the path forward.<br/><br/>Embark on a journey through the corridors of deep learning with "AI Foundations of Neural Networks." Unlock the secrets behind the artificial intelligence technologies that are transforming our world. Your exploration of neural networks starts here.<br/><br/>Perfect for: Students, AI professionals, tech enthusiasts, and anyone curious about the inner workings of neural networks and deep learning." —Provided by the publisher |
| 521 ## - TARGET AUDIENCE NOTE |
|---|
| Target audience note |
Adult |
| 541 ## - IMMEDIATE SOURCE OF ACQUISITION NOTE |
|---|
| Source of acquisition |
Purchased |
| Deans/Chairperson |
Ortega, Eric |
| Department |
College of Computer Studies |
| Subject Category |
Computer Science |
| 546 ## - LANGUAGE NOTE |
|---|
| Language note |
Text in English |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Neural networks (Computer science). |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Machine learning. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Type of record |
Subject Reference |
| 998 ## - LOCAL CONTROL INFORMATION (RLIN) |
|---|
| Encoded by |
Gian [new] |
| Date encoded |
08/24/2026 |
