As you are aware, since you've acquired this book, Python is the dominant programming language in AI. It has the richest ecosystem of all programming languages, including many implementations of state-of-the-art algorithms that make using them often a matter of simply importing and setting a few selected parameters. It should go without saying that we will go beyond the basic usage in many cases and we will talk about a lot of the underlying ideas and technologies as we go through the recipes.
We can't emphasize enough the importance of being able to quickly prototype ideas and see how well they work as part of a solution. This is often the main part of AI or data science work. A read-eval-print loop (REPL) is essential for quick iteration when turning an idea into a prototype, and you want functionality such as edit history, graphing, and more. This explains why Jupyter Notebook (where Jupyter is short for Julia, Python, R) is so central...
