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What is Machine Learning Techniques

Handbook of Research on Driving Socioeconomic Development With Big Data
Machine learning is part of the field of artificial intelligence (AI) which is used to derive patterns and regularities from a big set of data, including those hidden amongst the dataset variables (Wu et al., 2008 AU9: The in-text citation "Wu et al., 2008" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. ).
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Promises and Challenges Relating to Machine Learning Techniques to Predict Areas at Risk of Desertification: A State-of-the-Art Review
Marie-Isabelle von Schoenborn (ESCP Business School, Berlin, Germany) and Markus Bick (ESCP Business School, Berlin, Germany)
DOI: 10.4018/978-1-6684-5959-1.ch003
Land degradation and desertification are considered substantial issues in ecological and social research; hence the need for a quantitative, reliable, and repeatable methodology to evaluate desertification processes is urgent. This chapter aims to review the advances and limitations of existing work seeking to predict desertification through the use of automated, data-driven methods (i.e. machine learning). Using the CRISP-DM framework, existing research was classified into classic (supervised) ML models using field data, classic ML models using remote sensing data, and deep-learning models using remote sensing data. However, more research is needed to incorporate feedback effects and human intervention, as well as to make the distinction between desertification risk and desertification in ML models. Finally, the chapter suggests that existing research should be collated and formed into a “desertification warning system,” addressing the need to harmonize data, better understand desertification, and aim for the greater inclusion of local end-stakeholders.
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Machine Learning Models for Forecasting of Individual Stocks Price Patterns
A group of methods used to learn the past trading performance of various stocks used in this chapter.
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Semantic Video Analysis and Understanding
Training-based techniques for discovering and representing implicit knowledge, such as complex relationships and interdependencies between numerical image data and perceptually higher-level concepts.
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Education in the Era of Industry 4.0: Qualifications, Challenges, and Opportunities
This technique provides an ability to computer to learn without being explicit human intervention.
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