blparker

You can approach this in two stages:

1) Reacclimating yourself with the language. When I'm trying to pick up a a new language or re-engage with a language, I like to work on bite sized problems to understand the syntax and get somewhat comfortable with writing in it. I like to focus on the language and not worry too much about environment setup, best practices, frameworks, etc. You can easily do this by solving some Leetcode/Project Euler problems and running the code in Repl.it.

2) Working through a project. You're going to get the most value out of the time if you try to actually build something. The issue with step 1 above is that it doesn't teach you how things like package management, environment setup, testing, etc. work. It's going to be very slow at first, and you might end up restarting the project several times based on updated learning (which is good).

As it related to Python specifically, fortunately there's loads of very solid information available online. I'd pick one of the well-known frameworks (Django or Flask) and just start trying to build something with it.

Purposefully boring as to not become a distraction. Personally, my current unsexy setup is Django, Vue, and Bootstrap.

Thanks for sharing your story. Your experience is key—there may be a strong luck component to success, but with enough attempts, it seems that your luck increases. Often, hidden behind "overnight successes" is a trail of failures.

Chicago?

Apologies. Should be there now. I can reach out also.

I’m also self studying mathematics on the path to a “DIY statistics degree” (currently revisiting Calculus as well). I imagine there is a fair bit of overlap between what you’re doing. Would be interested in hearing more about how you’re handling your education journey.

Don’t have an active project at the moment, but would be interested in brainstorming potential ideas. Have experience throughout the stack and interested in areas of ML, AI, and Crypto. Feel free to reach out if you’re interested in potentially collaborating.

I’m doing something similar, except for Stats. I’ve cobbled together a plan based on degree programs from Stanford, CMU, and Berkeley. It would seem easier to stay on track with directed course learning, but how do you stay on track with the self-directed learning?

I've unfortunately experienced that smoker's anxiety of watching the clock and counting backwards, which takes the fun out of it. After probably thousands of cooks, I've learned to give myself way more time than I need mainly to account for fussy pieces of meat, trimming taking longer than expected, etc. I also tend to cook more forgiving pieces of meat like pork butt. Pork butt is remarkable because you can spend as little or much time prepping it as you want, letting it rest as long as you want, and it still comes out great.

Are the videos generally applicable or mainly to Ruby developers?

This seems like a reasonable idea.

Is the RAM in newer iMac models upgradable or is it soldered to the motherboard?

Working on a book/guide for developers about the mathematics behind machine learning with an aim towards intuition. All of the concepts are implemented in Python.

Any advice to an inexperienced person interested in getting started in aqua/aero-ponics?