Hands-On Artificial Intelligence for Banking: A practical guide to building intelligent financial applications using machine learning techniques

**** The reviewed product is an insightful and practical book that explores the intersection of Artificial Intelligence (AI) and the banking industry. It offers readers a significant amount of content, covering two primary sections: an overview of AI's role in the financial sector and a detailed look at Machine Learning with practical examples. The book facilitates an understanding of advanced concepts without delving deeply into complex coding, making it accessible to both banking professionals and individuals with technical backgrounds who wish to explore opportunities in the financial realm. One of the book's standout features is its inclusion of real-world examples, like sentiment analysis tutorials that guide readers through the process of analyzing social media data using Python. Additionally, the provision of downloadable code and references to external resources, such as the Open Bank Project and MongoDB, enhances its practicality. Its concise length, at 270 pages, allows for a quick read, though some reviewers noted that the breadth of content might warrant a more segmented approach, perhaps suggesting separate volumes for retail and investment banking. Readers acknowledged that the book serves as a valuable reference for those who want to understand how to apply AI solutions within their banking operations. It demystifies the concept of AI and demonstrates how average bankers can leverage open-source libraries to tackle typical challenges, including demand forecasting and risk assessment. Although it could benefit from additional local context or deeper coverage of topics, the book fundamentally enriches the reader's perspective on AI applications in banking. **