Torrent details for "Ertel W. Introduction to Artificial Intelligence 3ed 2024" Log in to bookmark
Controls:
×
Report Torrent
Please select a reason for reporting this torrent:
Your report will be reviewed by our moderation team.
×
Report Information
Loading report information...
This torrent has been reported 0 times.
Report Summary:
| User | Reason | Date |
|---|
Failed to load report information.
×
Success
Your report has been submitted successfully.
Checked by:
Category:
Language:
None
Total Size:
12.9 MB
Info Hash:
7B1E2FB1B298ADF64F02CE12915D87B3FFA354BA
Added By:
Added:
April 22, 2026, 2:26 p.m.
Stats:
|
(Last updated: April 22, 2026, 2:26 p.m.)
| File | Size |
|---|---|
| ['Ertel W. Introduction to Artificial Intelligence 3ed 2024.pdf'] | 0 bytes |
Name
DL
Uploader
Size
S/L
Added
-
12.9 MB
[19
/
23]
2026-04-22
| Uploaded by andryold1 | Size 12.9 MB | Health [ 19 /23 ] | Added 2026-04-22 |
NOTE
SOURCE: Ertel W. Introduction to Artificial Intelligence 3ed 2024
-----------------------------------------------------------------------------------
COVER
-----------------------------------------------------------------------------------
MEDIAINFO
Textbook in PDF format This accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks, and reinforcement learning. Fully revised and updated, this much-anticipated third edition also includes new material on deep learning. Topics and features: Presents an application-focused and hands-on approach to learning, with supplementary teaching resources provided at an associated website. Introduces convolutional neural networks as the currently most important type of deep learning networks with applications to image classification. (NEW) Contains numerous study exercises and solutions, highlighted examples, definitions, theorems, and illustrative cartoons. Reports on developments in deep learning, including applications of neural networks to large language models as used in state-of-the-art chatbots as well as to the generation of music and art. (NEW) Includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks, and reinforcement learning. Covers various classical machine learning algorithms and introduces important general concepts such as cross validation, data normalization, performance metrics and data augmentation. (NEW) Includes a section on AI and society, discussing the implications of AI on topics such as employment and transportation. Ideal for foundation courses or modules on AI, this easy-to-read textbook offers an excellent overview of the field for students of computer science and other technical disciplines, requiring no more than a high-school level of knowledge of mathematics to understand the material
×