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Machine Learning in Business Finance using Python

Author

Listed:
  • Kian Guan Lim

    (Singapore Management University, Singapore)

Abstract

This book is an introduction to machine learning using Python programming language with applications in finance and business. Coverages include the prediction methods of logistic regression, Naïve Bayes, k-Nearest Neighbor, Support Vector Machine, Random Forest, Gradient Boosting, and various types of Neural Networks. Performance measurements and assessments of feature importance are also explained. The book also contains detailed examples of the applications with data. Python codes are explained in a step-by-step manner using Jupyter Notebook so that the readers can practise on their own.

Suggested Citation

  • Kian Guan Lim, 2025. "Machine Learning in Business Finance using Python," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 14271, March.
    • Handle: RePEc:wsi:wsbook:14271
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    File URL: https://www.worldscientific.com/worldscibooks/10.1142/14271
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    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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