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Hands-On Artificial Intelligence for Banking

You're reading from  Hands-On Artificial Intelligence for Banking

Product type Book
Published in Jul 2020
Publisher Packt
ISBN-13 9781788830782
Pages 240 pages
Edition 1st Edition
Languages
Authors (2):
Jeffrey Ng Jeffrey Ng
Profile icon Jeffrey Ng
Subhash Shah Subhash Shah
Profile icon Subhash Shah
View More author details

Table of Contents (14) Chapters

Preface 1. Section 1: Quick Review of AI in the Finance Industry
2. The Importance of AI in Banking 3. Section 2: Machine Learning Algorithms and Hands-on Examples
4. Time Series Analysis 5. Using Features and Reinforcement Learning to Automate Bank Financing 6. Mechanizing Capital Market Decisions 7. Predicting the Future of Investment Bankers 8. Automated Portfolio Management Using Treynor-Black Model and ResNet 9. Sensing Market Sentiment for Algorithmic Marketing at Sell Side 10. Building Personal Wealth Advisers with Bank APIs 11. Mass Customization of Client Lifetime Wealth 12. Real-World Considerations 13. Other Books You May Enjoy

To get the most out of this book

Before you get started, I assume that you are running Ubuntu 16.04LTS Desktop or above and have done your Python 101 course. Knowledge of how to install the relevant software packages is assumed and will not be covered in this book.

Three database engines (SQLite, MongoDB, and Neo4j) are used in this book. Please make sure that you have them installed.

Regarding data sources, we will get data from data.world (https://data.world/) and a paid subscription to Quandl (Sharadar Core US Equities Bundle (https://www.quandl.com/databases/SFA/data) for chapters 4 and 5, and Sharadar Fund Prices (https://www.quandl.com/databases/SFP/data) for chapters 6 and 7), Twitter's Premium Search (https://developer.twitter.com/en/docs/tweets/search/overview/premium) for chapter 7, and the Open Bank Project (https://uk.openbankproject.com/) for chapter 8.

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