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blparker

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hnchat:bDaGtGkwZHizIGvy5ul6

Email: bryan.parker24@gmail.com

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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.

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.

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.

IBM | Software Engineer (Predictive Analytics) | Chicago, IL | ibm.com

I'm an engineer on the predictive analytics team in Chicago, and we're looking to expand our team by adding engineers. We work with data scientists and researchers to research, define, and implement predictive modeling algorithms to surface insights in customer's data. Engineers of all experience levels welcome. If you'd like more info, feel free to let me know or check out the listings here:

https://careers.ibm.com/ShowJob/Id/709792/Software-Engineer-...

https://careers.ibm.com/ShowJob/Id/709790/Software-Engineer-...

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.

IBM | Software Engineer (Predictive Analytics), Data Scientist | Chicago, IL | ibm.com

The predictive analytics team in Chicago is looking to add a software engineer and data scientist to a small, but growing team. We work with data scientists and researchers to research, define, and implement predictive modeling algorithms to ultimately surface insights in customer's data.

See more here:

  - https://careers.ibm.com/ShowJob/Id/419192/?lang=en (software engineer)
  - https://careers.ibm.com/ShowJob/Id/416940/?lang=en (data scientist)

I think having this "barrier to entry" is important. When I have an idea, I tend to let it sit and re-evaluate after the "lust" stage has died down. Often times, I realize perhaps it wasn't as cool as I thought. If something is still nagging at your days later, perhaps it's a good candidate to evaluate.

Regarding your last point, I think also what a lot of developers struggle from (myself included) is project ADD. Having discipline to scope something out, set sane (and near) deadlines and focus only on that is important to seeing it through to completion. Good work on developing that discipline.

That's great, but I think this is even more accomplished than a majority of developers. The majority of developers have a wild or fun sounding idea and pursue it for a few days (guilty of this myself). Most likely, the "fun" part only constitutes a minority of overall functionality, and I find it's generally the non-fun stuff that demotivates people to not finish (e.g., billing, setting up a web site, user management, etc.) The key has to be to either determine if those things are critical, or somehow fit them in before you're left with nothing other than a pile of non-fun stuff.

I'm interested in that last statement regarding aspartame. It seems you find extremely polarized opinions on artificial sweeteners. I've often read that, regardless of the health impact (or lack thereof), artificial sweeteners are more-or-less "tricking" your body into thinking it has calories incoming, when in fact, it doesn't. Your body, feeling jipped, tries to compensate by craving more calories. But, again, this is hearsay.

What I've been able to gather over the years (and in this thread) and pretty much what I've incorporated into my diet is the following:

  - Avoid processed foods
  - Avoid added sugars
  - Limit fruit intake (especially those high in fructose) and especially avoid fruit juices
  - Avoid simple carbs (e.g., bread, tortillas, flour) and look to lower carb intake in general (~300g daily limit seems excessive)
  - Eat more meals composed of higher fat/protein and a vegetable (e.g., protein and a vegetable)
  - Fats aren't as bad as people believe
When it's all said and done, I think you're right though. The fact of the matter is we all love carbs and sugar way too much. We need to eat more plants.

After reading these comments, I'm more confused than entering. Throughout the years, we've constantly been subjected to advertising from fad diets claiming low-fat or low-carb or no-grain or no-sugar or low-whatever is the magic elixir to being healthy and losing weight. It seems that every nutritionist you talk to has a subjective bias as to the key. I understand that the body is an incredibly complex machine, and it's probably impossible to distill things down into a set of manageable steps, but I would just like to know what to eat, what not to eat, some simple science as to why, and not have bullshit or biases injected into the conversation.