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lebeaudiable t1_j32cx1s wrote

Thank you for the advice. I fell into development during the pandemic and it’s been my new area of interest ever since. Being a full-stack dev is just a personal goal of mine. I am planning on learning more about ML in general after I finish reading/following along with the NLTK book, and I will likely take a course. Do you recommend any SPECIFIC materials? I know what’s commonly recommended via wiki and search, but I’m curious to know what you’re using and reading in your program or what you’d recommend in general, personally.

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StackOwOFlow t1_j33kwse wrote

As a domain expert, you’d probably want to focus specifically on feature engineering if you’re looking to continue training the existing model or new models. A lot of it comes down to asking good questions and hypothesis testing informed by knowledge of the law that you already have.

Figuring out how to use those models in real-world applications employs a different skillset, however, and that sounds more like what your original question is asking about. You’d probably get a better sense of this through examples of applications that intro to ML courses reference and surveying ML-driven applications in various industries. Here's a good hands-on resource: https://machinelearningmastery.com/start-here

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