Analysis of machine learning methods applied to financial problems

With machine learning being widely used in many fields. In this paper, we study how machine learning methods can be used to make predictions in financial problems and analyze the applications.Machine learning is a branch of artificial intelligence that enables computer systems to learn from data and make decisions or predictions without being explicitly programmed at every step. Machine learning models are trained on large amounts of data to discover patterns and relationships in the data and use these patterns to make predictions or perform tasks. The purpose of this post is to illustrate the role machine learning plays in dissertation research.Machine learning can also be used for smart urbanization, industrial automation, fintech, healthcare, agricultural modernization, cybersecurity, etc. For example, extracting valuable information and knowledge from large amounts of data to help businesses and organizations make better decisions. By analyzing historical data, machine learning can predict future trends and behaviors, such as stock prices, house prices, weather, etc.

Authors

Publication Details

Journal
Transactions on Computer Science and Intelligent Systems Research
Published
2024-10-17
DOI
https://doi.org/10.62051/erpm8q62
Citations
1
Primary Topic
Stock Market Forecasting Methods
Type
article
Field-Weighted Citation Impact
0.49
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article

Analysis of machine learning methods applied to financial problems

Jiayi Zhang
1 citations
Transactions on Computer Science and Intelligent Systems Research
Stock Market Forecasting Methods
0.49
article

Analysis of machine learning methods applied to financial problems

Jiayi Zhang
article en
1 citations

Abstract

With machine learning being widely used in many fields. In this paper, we study how machine learning methods can be used to make predictions in financial problems and analyze the applications.Machine learning is a branch of artificial intelligence that enables computer systems to learn from data and make decisions or predictions without being explicitly programmed at every step. Machine learning models are trained on large amounts of data to discover patterns and relationships in the data and use these patterns to make predictions or perform tasks. The purpose of this post is to illustrate the role machine learning plays in dissertation research.Machine learning can also be used for smart urbanization, industrial automation, fintech, healthcare, agricultural modernization, cybersecurity, etc. For example, extracting valuable information and knowledge from large amounts of data to help businesses and organizations make better decisions. By analyzing historical data, machine learning can predict future trends and behaviors, such as stock prices, house prices, weather, etc.

Transactions on Computer Science and Intelligent Systems ResearchVol. 6
Sustainable cities and communities
Openalex Percentile: Top 30%
Stock Market Forecasting Methods
0.49
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Analysis of machine learning methods applied to financial problems — Jiayi Zhang · Transactions on Computer Science and Intelligent Systems Research (2024) | TGRS Research Map | TGRS