I'm wondering if this would be suitable for learning financial analysis with python. I'm mostly interested in ways to model expenses, investments, and retirement cash flows based on historical data as input.
Also, I'm wondering what environment you recommend using for your code examples. Is Jupyter Notebook the sweet spot, or did you have another programming environment in mind?
I do mention financial trading as an application in the introduction, but didn't get to write a chapter on it! This is partially because I know very little about this, and I didn't want to mislead anyone on their financial decisions . However, you should be able to read chapters 14-16 and get some good ideas for how you might apply machine learning to make decisions about investments.
I use Jupyter for all my code examples. You can find my complete notebooks with all code from the book on my GitHub. Jupyter notebooks are great for doing mathematical/data analysis, because they allow you to re-run small parts of your program and fix computations until you get it right. They also allow you to put graphs inline, which is not possible in the terminal!
Of course, if you're building some production software system (like a program to trade stocks for you) you probably will want to write a standalone program/script rather than a notebook.
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