| Description |
1 online resource |
|
text file |
|
PDF |
| Note |
Includes index. |
| Contents |
Introduction -- Linear continuous models -- Hidden linear continuous models -- Linear network models -- Classic discrete models -- Classic mixed models -- Advanced techniques. |
| Summary |
Discover the art and science of solving artificial intelligence problems with Python using optimization modeling. This book covers the practical creation and analysis of mathematical algebraic models such as linear continuous models, non-obviously linear continuous models, and pure linear integer models. Rather than focus on theory, Practical Python AI Projects, the product of the author's decades of industry teaching and consulting, stresses the model creation aspect; contrasting alternate approaches and practical variations. Each model is explained thoroughly and written to be executed. The source code from all examples in the book is available, written in Python using Google OR-Tools. It also includes a random problem generator, useful for industry application or study. You will: Build basic Python-based artificial intelligence (AI) applications Work with mathematical optimization methods and the Google OR-Tools (Optimization Tools) suite Create several types of projects using Python and Google OR-Tools. |
| Subject |
Python (Computer program language)
|
|
Artificial intelligence.
|
|
Python (Langage de programmation) |
|
Intelligence artificielle. |
|
artificial intelligence. |
|
Mathematical theory of computation. |
|
Computer programming -- software development. |
|
Programming & scripting languages: general. |
|
Artificial intelligence |
|
Python (Computer program language) |
| Other Form: |
Print version: 1484234227 9781484234228 (OCoLC)1013727195 |
| ISBN |
9781484234235 (electronic bk.) |
|
1484234235 (electronic bk.) |
| Standard No. |
10.1007/978-1-4842-3423-5 doi |
| Report No. |
SPRINTER |
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