There you can find the prompt that allowed ChatGPT to provide a working solution. It is a bit hit and miss, but you also gotta make sure any assumptions are explicitly noted in the prompt.
I don't want to get a MSc or PhD, only because I don't think it is worth the time. I like some aspects of academia, but I much prefer learning things by myself.
That said, I have a strong desire to learn math, and I have a copy of Understanding Analysis waiting for me to pick up. I think I'd like to learn Analysis, Linear Algebra, Probability, Graphs... Book suggestions are welcome by the way.
- Linear Algebra: Gilbert Strang's book + MIT OCW video series. Alternatively/additionally Sheldon Axler's Linear Algebra Done Right. Must watch 3blue1brown series on LinAlg.
- Analysis: Spivak's Calculus (yes). Understanding Analysis is also supposed to be good.
- Probability: Introduction to Probability by Dimitri Bertsekas and John Tsitsiklis.
- Graphs: Plenty nice books. Can also choose GT specific chapters from Discrete Math books.
Edit: If you haven't have formal Math training, you need to learn how to write proofs. For Proofs, I wholeheartedly recommend Jay Cummings's book "Proof: A Long Form Text Book".
For analysis you can't go wrong with Rudin, especially if you already will have experience from Understanding Analysis. For graph theory I quite liked Diestel, but that may not be the best introductory text.
I use a combination of both. Logging usually requires less setup overhead, so I often opt for that. Sometimes though, the path it takes for the code to reach the part I'm interested in can be pretty obscure. It's in these cases that the debugger truly shines.
It also depends on how many things you are interested in. If you care about, say, a complex object with many properties, then the interactivity of a debugger trumps logging.
> Sometimes though, the path it takes for the code to reach the part I'm interested in can be pretty obscure. It's in these cases that the debugger truly shines.
I feel that it is the opposite. It is where the path is obscure that logging works really well. It can be iteratively refined and repeated.
There you can find the prompt that allowed ChatGPT to provide a working solution. It is a bit hit and miss, but you also gotta make sure any assumptions are explicitly noted in the prompt.