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.
Yes, exactly. You'll be surrounded by succeeding and failing people, and you'll see patterns in decision making, execution and (in)valiations. It helps tremendously. Also, I'm feeling very confident in my position and execution because I've suffered enough over the past years. So current challenges feel much easier.
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.
As a brief summary, I spend a couple hours every day working through a textbook. In choosing what/how to study in mathematics I'm driven by two considerations: 1. It's important to master the basics before anything else. So I need to cover linear algebra (done) and calculus (WIP) 2. Beyond the basics, I'm driven by curiosity/play. My current interests lie mostly in stats and physics.
Happy to chat otherwise, I put my email in my profile.
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.
Hi, I have been working on a trading bot for crypto in rust for the last ~18 months. The agent and the infrastructure (collecting and preprocessing data) are up and running. I have been collecting and cleaning TBs (yes TBs) of data for ~1 year now. However, I have way too little knowledge in ML/AI and it is very hard to fill the gap. I am looking for someone that can help me in that area and improve the bot to leverage the data using some ML/AI. I can provide more info. Contact info should be available in the profile.
Can’t figure out a way to contact you from your About section —- I’m a ML engineer with an early interest in algorithmic trading, would be interested in brainstorming ideas.
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.
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.