Forwarded from Soset Hub
ααα«α α°αα α΅π
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Forwarded from Kidus's Chronicles
I built Haven to solve one of the big problems in the world, currently under development and patenting the product (there is a physical product) where women can wear anywhere. We are working with multiple organisations to make this freely available to every body, the reason we are even trying to patent it
haven.kidus-yohannes.engineer
HAVEN β Women's Safety SOS
HAVEN is a women's safety platform that sends emergency SOS alerts with audio, photo, and GPS to your contacts and police instantly.
Sometimes, when you feel too comfortable, pause and ask yourself: βIs something wrong?β
One thing Iβm learning is that our habits donβt 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 youβre always choosing what feels easy, maybe itβs worth looking at where that choice is taking you.
And sometimes, the uncomfortable choice is exactly the one that helps you grow.
#Mindset
@next_commit
One thing Iβm learning is that our habits donβt 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 youβre always choosing what feels easy, maybe itβs 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
@next_commit
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.
π Live demo: https://fayda-decoder.alphalabshq.com
π GitHub: https://github.com/Alpha-Mintamir/fayda-decoder (star the repoβοΈ π«Ά )
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
π Live demo: https://fayda-decoder.alphalabshq.com
π 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:
π₯ Home screen widget : See your streak without opening the app.
π¨ Themes : Make your contribution graph yours. Dev-coded, bold, soft - pick your vibe.
π₯ Friends : Compare grids and keep each other shipping.
Try it out β LINK
Letβs see whoβs actually shipping.
@eyudevs
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:
π₯ Home screen widget : See your streak without opening the app.
π¨ Themes : Make your contribution graph yours. Dev-coded, bold, soft - pick your vibe.
π₯ Friends : Compare grids and keep each other shipping.
Try it out β LINK
Letβs see whoβs actually shipping.
@eyudevs
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: π₯ Home screen widget : See your streak without opening the app. π¨ Themesβ¦
Omg, I really like this app π₯ Seeing other peopleβs streaks actually makes me want to commit more Now I can finally keep an eye on your GitHub streak too π
The UI is so good tho⦠I should to start learning UI
The UI is so good tho⦠I should to start learning UI
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
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.
π https://huggingface.co/datasets/snapwre/amharic-speech
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.
π https://huggingface.co/datasets/snapwre/amharic-speech
huggingface.co
snapwre/amharic-speech Β· Datasets at Hugging Face
Weβre on a journey to advance and democratize artificial intelligence through open source and open science.
π₯1
Chapi Dev Talks
BIG UPDATE ON DATASET.ET
WE GOT A 10k USD from AWS from NVIDEA INCETPTION.
WE GOT A 10k USD from AWS from NVIDEA INCETPTION.
Woah, i didn't expect this, it's a big Wπ₯