LearnOptima
Learn anything, with a real plan built just for you
What it does
Most learning apps use one-size-fits-all content and hope it's right, leaving you with another half-finished course. LearnOptima builds one sequenced 30-lesson roadmap per skill, personalized to your actual level, pace, and learning style, not a generic path everyone gets. Lessons are grounded in real retrieved sources, articles, docs, and videos, with theory, a hands-on exercise, and a quiz each day. Pass to unlock the next lesson. Try a real Day 1 lesson free, no card needed.
Free 3-minute quiz, your finish strategy, and a real Day 1 lesson before signup. One skill. 30 daily lessons. Pass each day to unlock the next.
Take a 3-minute quiz. Get your learning profile and finish strategy, then try a real Day 1 lesson free before you create an account. Answer 5 quick questions first. We analyze your fit, set your style and session length, then you pick your experience level before your Day 1 preview. This calibrates lesson depth from beginner scaffolding to advanced depth. Pick what matches you today. Your style, session length, and experience level are set. Confirm your skill, 30-day goal, and desired outcome. One free preview per email. We'll save your lesson and send a resume link. A real lesson from the same system as full roadmaps: theory, exercise, and quiz. Building your Day 1 lesson from your skill,…from learnoptima.online
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Hello HN, Over the last 12 months, I have been building https://learnawesome.org This idea came from Danny Hillis' 2012 talk at OSCON, which itself was inspired from Neal Stepehenson's _The Diamond Age : A Young Lady's Illustrated Primer_ The dream is to build a tool that matches the right learning material to the right student at the right time. Wikipedia is great, but it doesn't do a good job of leveraging the rich variety of learning resources that exist on the Web. Same applies to GoodReads - which is focused only on books, whereas these days we actually learn from videos,…
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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