The essentials of machine learning in finance and accounting
Author(s)
Bibliographic Information
The essentials of machine learning in finance and accounting
（Routledge advanced texts in economics and finance）
Routledge, 2021
- : pbk
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
* A useful guide to financial product modeling and to minimizing business risk and uncertainty
* Looks at wide range of financial assets and markets and correlates them with enterprises' profitability
* Introduces advanced and novel machine learning techniques in finance such as Support Vector Machine, Neural Networks, Random Forest, K-Nearest Neighbors, Extreme Learning Machine, Deep Learning Approaches and applies them to analyze finance data sets
* Real world applicable examples to further understanding
Table of Contents
1. Machine Learning in Finance and Accounting 2. Decision Trees and Random Forests 3. Improving Longevity Risk Management through Machine Learning 4. Kernel Switching Ridge Regression in Business Intelligence 5. Predicting Stock Return Volatility using Sentiment Analysis of Corporate Annual Reports 6. Random Projection Methods in Economics and Finance 7. The Future of Cloud Computing in Financial Services: A Machine Learning and Artificial Intelligence Perspective 8. Prospects and Challenges of Using Artificial Intelligence in Audit Process 9. Web Usage Analysis: Pillar 3 Information Assessment in Turbulent Times 10. Machine Learning in the Fields of Accounting, Economics and Finance: The Emergence of New Strategies 11. Handling Class Imbalance Data in Business Domain 12. Artificial Intelligence (AI) in Recruiting Talents Recruiters' Intention and Actual Use of AI
by "Nielsen BookData"