welcome
Thank you for purchasing the MEAP for Advanced Analytics for Business: Generative AI and machine learning for tabular data. To get the most benefit from this book, you’ll want to have some established skills in Python programming, with experience in basic machine learning models and beginners knowledge of deep learning.
Every bank, every insurance company, every government agency, every retailer, every manufacturer - all of them run on data organized in rows and columns, that is, tabular data. As you live a modern life as a consumer, an employee and a citizen, your daily activities generate updates in hundreds, even thousands, of tables. Think of the possibilities if you could apply machine learning to unlock new insights about tabular data, the kind of data that you work with in your job every day. We wrote this book to give you the skills, tips, and best practices to do just that: apply machine learning to solve tabular data problems.
For the last decade, deep learning has dominated machine learning across a wide range of data types, including images, text, audio, and video. However, deep learning is still not triumphant in one key area: tabular data. In this book, we will explain why deep learning isn’t yet the go-to solution for tabular data problems. We'll also discuss the power of classic machine learning approaches, particularly gradient boosting, when it comes to tabular data, and the circumstances where you might want to choose one approach over the other.