π™½πšŽπš‘πš π™²πš˜πš–πš–πš’πš
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No guru stuffβ€”just sharing what I'm learning, what I'm building, and the lessons along the way. ✨

If you vibe with it, give the channel a boost ⚑️
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Sometimes, when you feel too comfortable, pause and ask yourself: β€œIs something wrong?”
One thing I’m learning is that our habits don’t always show their consequences immediately.
Bad habits can feel good now but cost you later.

Good habits can feel uncomfortable now but reward you later.
So if you’re always choosing what feels easy, maybe it’s worth looking at where that choice is taking you.
The comfort you enjoy today might be the price you pay tomorrow.

And sometimes, the uncomfortable choice is exactly the one that helps you grow.

#Mindset

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Forwarded from Alpha Labs
Soo, I run a scooter rental business. Every rental starts with checking the customer's Fayda ID and typing their details into our system by hand. Slow, and full of typos.

The proper fix is the Fayda API. We tried. The bureaucracy defeated us before we ever got a key.

Then I realized the card already carries everything: the QR on the back holds the holder's name, gender, FAN, date of birth, face photo, and NIDP's digital signature.

So I built the missing piece and open sourced it.

fayda-decoder turns that QR into clean JSON from a simple photo of the card. It even verifies NIDP's cryptographic signature, so printed fakes fail instantly.

100% on-device, browser or Node. Nothing is uploaded anywhere.

Reads blurry, dark, photos that normal QR scanners reject. Decodes in under 100 ms.
No API key, no approval process, no permission needed.

npm install fayda-decoder


πŸ‘‰ Live demo: https://fayda-decoder.alphalabshq.com

πŸ‘‰ GitHub: https://github.com/Alpha-Mintamir/fayda-decoder (star the repo ⭐️🫢)
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Forwarded from Eyu Devs
INTRODUCING GITSTREAK

It's pretty self-explanatory.

Open β†’ see your grid β†’ feel the momentum β†’ close.

Under 5 seconds. No login. No ads. No complicated dashboards.

What makes it stick:
πŸ”₯ Home screen widget : See your streak without opening the app.
🎨 Themes : Make your contribution graph yours. Dev-coded, bold, soft - pick your vibe.
πŸ‘₯ Friends : Compare grids and keep each other shipping.

Try it out β†’ LINK

Let’s see who’s actually shipping.

@eyudevs
Forwarded from Kidus's Chronicles
The ML Roadmap is finally live.
When I started learning ML, the hardest part wasn't the math or the code. It was not knowing what to learn next. I ended up learning everything I could find, and honestly a good chunk of it I never use. Along the way I kept notes on the parts that actually mattered, and this roadmap came out of those notes plus a lot of research on how to order the nodes properly, from fundamentals all the way to deployment.
What's in it: a checklist at every node, questionnaires to test yourself, over 80 curated resource links, and real projects built on actual datasets. It starts by figuring out where you already are and points you to the right node instead of making you start from zero. Nodes stay locked until you finish the one before it, so the path stays honest.
This is the first version and it will keep growing. I'd like to hear what the experience feels like, what's missing, and what you'd want added.

Check it live at : Link
Forwarded from Chapi Dev Talks
We're releasing the first batch of Dataset.ET open speech data for Amharic.

22.7 hours. 7,405 recordings. 320 speakers. Free, CC BY 4.0, on Hugging Face.

Amharic has close to no open speech data. That's the gap we're trying to close, and this is the first step rather than the finished thing.

Some honesty about what this is: it's a first batch. The audio isn't preprocessed yet. We're not going to tell you it's the best quality out there. We don't think it is. What we want is for people to actually use it and tell us where it falls short.

The next release will be different: properly preprocessed audio, a real data pipeline with testing and validation built in. This exists because 320 people in Ethiopia gave their voices to it, and because contributors reviewed each other's recordings. Thank you to all of them.

If you're working on Ethiopian languages, low-resource ASR, or you just want to talk about the data, DM us. We'd genuinely like to hear from you.

πŸ”— https://huggingface.co/datasets/snapwre/amharic-speech
πŸ”₯1
From YC Startup School β€” Before the Startup by Paul Graham
A few ideas that genuinely made me stop and think:
1. Starting early β‰  starting in college.
Startups can consume your entire life. Your early 20s can be better spent exploring, learning, experimenting, and figuring out what actually matters to you.
2. Don’t chase startup ideas.
The best ideas can come from simply learning deeply, working on interesting problems, and building things.
Sometimes you discover the idea instead of searching for it.
3. Don’t need to be a startup expert.
What matters more is becoming an expert in the problem and the users I’m trying to solve for.
The startup mechanics can be learned when needed.
4. Don’t optimize for the GPA.
Learn difficult and powerful things because you’re genuinely curious.
Users don't care about our GPA. YC doesn't either.
One line I’m taking from today:
Don’t try to become a founder. Become someone who knows something deeply and can build something people want.

🀞 Just learn.

#KeepLearning

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πŸ”₯2