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International Series in Operations Research and Management Science Ser.: Machine - Picture 1 of 1
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International Series in Operations Research and Management Science Ser.: Machine

MNJWATSON
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Item specifics

Condition
Brand new: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
ISBN
9783030774844

About this product

Product Identifiers

Publisher
Springer International Publishing A&G
ISBN-10
3030774848
ISBN-13
9783030774844
eBay Product ID (ePID)
13050400415

Product Key Features

Book Title
Machine Learning and Artificial Intelligence for Agricultural Economics : Prognostic Data Analytics to Serve Small Scale Farmers Worldwide
Number of Pages
Xix, 599 Pages
Language
English
Publication Year
2021
Topic
Probability & Statistics / General, Operations Research, Industries / Agribusiness
Illustrator
Yes
Genre
Mathematics, Business & Economics
Author
Chandrasekar Vuppalapati
Book Series
International Series in Operations Research and Management Science Ser.
Format
Hardcover

Dimensions

Item Weight
38.3 Oz
Item Length
9.3 in
Item Width
6.1 in

Additional Product Features

Dewey Edition
23
Series Volume Number
314
Number of Volumes
1 vol.
Dewey Decimal
338.1028563
Table Of Content
1. Introduction.- 2. Data Engineering and Exploratory Data Analysis Techniques.- 3. Agricultural Economy and ML Models.- 4. Commodity Markets - Machine Learning Techniques.- 5. Weather Patterns and Machine Learning.- 6. Agriculture Employment and the Role of AI in improving Productivity.- 7. Role of Government and the AI Readiness.- 8. Future.
Synopsis
1. Introduction.- 2. Data Engineering and Exploratory Data Analysis Techniques.- 3. Agricultural Economy and ML Models.- 4. Commodity Markets - Machine Learning Techniques.- 5. Weather Patterns and Machine Learning.- 6. Agriculture Employment and the Role of AI in improving Productivity.- 7. Role of Government and the AI Readiness.- 8. Future., This book discusses machine learning and artificial intelligence (AI) for agricultural economics. It is written with a view towards bringing the benefits of advanced analytics and prognostics capabilities to small scale farmers worldwide. This volume provides data science and software engineering teams with the skills and tools to fully utilize economic models to develop the software capabilities necessary for creating lifesaving applications. The book introduces essential agricultural economic concepts from the perspective of full-scale software development with the emphasis on creating niche blue ocean products. Chapters detail several agricultural economic and AI reference architectures with a focus on data integration, algorithm development, regression, prognostics model development and mathematical optimization.Upgrading traditional AI software development paradigms to function in dynamic agricultural and economic markets, this volume will be of great use to researchers and students in agricultural economics, data science, engineering, and machine learning as well as engineers and industry professionals in the public and private sectors.
LC Classification Number
T57.6-.97

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