Summary

We have just completed the entire book of The Applied Artificial Intelligence Workshop, Second Edition. In this workshop, we have learned about the fundamentals of AI and its applications. We wrote a Python program to play tic-tac-toe. We learned about search techniques such as breadth-first search and depth-first search and how they can help us solve the tic-tac-toe game.

In the next couple of chapters after that, we learned about supervised learning using regression and classification. These chapters included data preprocessing, train-test splitting, and models that were used in several real-life scenarios. Linear regression, polynomial regression, and support vector machines all came in handy when it came to predicting stock data. Classification was performed using k-nearest neighbor and support vector classifiers. Several activities helped you to apply the basics of classification in an interesting real-life use case: credit scoring.

In Chapter 4, An Introduction...