Gooooood morning beautiful people

Daily Reminder,
Give yourself permission to let go of what weighs heavily on your soul. You carry it all so well, but that does not mean that it is yours to hold.

Have a spectacular day ✨

#DailyReminder @kiduschronicless

May our day as beautiful as this flowers 💐 ✨️ 💕 also as powerful as the 🌞 ☀️ sun

When they started the meeting like this🤭😁😁 I forget what have prepared for and what am going to speak then I vibe with the music 🎶 🎵 😌 ☺️☺️😁

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"If this isn't for you, please share it with others who might be interested."🙏

Follow us👇for more opportunities
@opportunity_alerts

Good morning my habesha people ✌️😊 It is another day It is the 4th Day of the week let us begin the Day with the energy we had since we start the week🫡🫡 Happy Thursday

Check them out👍👍

https://careers.shega.co/jobs/6843855-shega-remote-internship-program-cohort-1-university-students-only

May our next summer ☀️ be like this☺️☺️😎😎

Hey guys , How was your day ?

I couldn't get enough time to share in detail what I've been working on lately, but now that I've finally submitted and completed the project, let me walk you through it.

Since it's a Machine Learning project, there isn't much fancy UI to look at 😅. The interesting part is the idea behind it.

Imagine services like Telebirr, mobile banking, digital loans, and online payments. Every day, thousands of transactions happen, and financial institutions need a way to identify customers who might be risky before offering loans or other financial services.

So I built a Credit Risk Prediction System.The system:
->Analyzes customer transaction history
->Learns patterns from historical data
->Estimates customer risk levels
->Provides predictions through an API

Think about it this way. When someone buys airtime, sends money, pays utility bills, uses Telebirr, or performs other digital transactions, all of those activities create a transaction history. The model studies these patterns and estimates how risky or trustworthy a customer is.

One thing that excites me is that this project was built using transaction data from another country. It makes me wonder what insights we could discover if we trained a similar model using actual Ethiopian transaction data from services like Telebirr and local financial institutions. 🤔

Good morning ppl 😊🫡 It is Friday
I don't know how the day move fast like this but here we are🤧
28/09/2018 E.C

Good morning ppl🫡🫡
Have a productive Day and weekend 🙌🙌

Your work can be amazing and still get ignored if nobody sees it. :))

CURSOR was giving away 1 year of Pro FOR FREE with student email

but Ethiopia isn't Eligible 😭

@byte_philosopher

Have blessed ሰንበት ya'll🤗

#thought_ofme