Career Crate
DSA, system design, GATE & govt jobs — for Indian engineers
What it does
Career Crate covers the full Indian engineering career journey in one place — DSA patterns for FAANG, system design for product companies, GATE CSE 2026 study plans, PSU & government job tracking (BHEL, NTPC, ISRO, ONGC), and daily fresher job alerts from top Indian companies. Most platforms are built for US hiring. Career Crate is built for Naukri, LinkedIn India, GATE, and PSU recruitment. Free for everyone.
Career Crate — India's all-in-one platform for SDE job prep. DSA problems, roadmaps, job board, mock interviews, contests, and more.
Curated jobs, 3000+ DSA problems, mock interviews, and a community of developers — all in one place. 3000+ problems with AI hints, CC-100 must-solve list, and step-by-step algorithm visualizer. Kanban board — track every application from wishlist to offer, with notes and deadlines. Salary negotiation, job switch strategy, offer comparison — built for Indian tech salaries. Ask questions, share knowledge, get advice from peers preparing for the same roles. Real stories from developers at Amazon, Google, Flipkart and 40+ Indian tech companies. OS, DBMS, Networks, OOP — spaced repetition that sticks. Review in 10 minutes afrom careercrate.online
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Life & fun · 10d ago · louisabraham.github.io
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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…
Life & fun · Aug 2026 · toneyalexander.github.io
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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