“Machine Learning and Data Science Blueprints for Finance” by Hariom Tatsat, Sahil Puri, and Brad Lookabaugh is a book that provides a practical guide to using machine learning and data science techniques in the finance industry.

The book is suitable for data scientists, financial analysts, and anyone who works with financial data and wants to learn how to use machine learning and data science to analyze and make predictions about financial markets and transactions.

The book covers a wide range of topics related to machine learning and data science in finance, including:

1. Introduction to machine learning and data science in finance
2. Data preprocessing and feature engineering techniques
3. Regression and classification algorithms for financial prediction
4. Time series analysis and forecasting using machine learning
5. Deep learning techniques for finance
6. Portfolio optimization and risk management using machine learning
7. Sentiment analysis and natural language processing for finance
8. Fraud detection and anomaly detection using machine learning

The book also includes practical examples and case studies to help readers apply the concepts in real-world scenarios. It emphasizes best practices in machine learning and data science, including data cleaning, model selection, and performance evaluation.

Overall, “Machine Learning and Data Science Blueprints for Finance” is a comprehensive guide to using machine learning and data science techniques in the finance industry. It is written in an accessible and easy-to-understand style and is suitable for anyone who wants to learn how to use machine learning and data science to make better financial decisions.