I was wondering about vs code and I found this article if u r curious... here 🤌 https://www.linkedin.com/pulse/from-origin-optimization-story-visual-studio-code-thirumoorthy-bqtxc/?trackingId=UWxtIt85Te2Q4g4fjrjrog%3D%3D it is short tho

Today, I came across RAG (Retrieval-Augmented Generation) while working on an assignment for 10 Academy.
You know, Large Language Models (LLMs) like GPT or DeepSeek are incredibly powerful, but they do have limitations—especially when it comes to domain-specific expertise or producing accurate responses in specialized contexts.

That’s where RAG comes in. It enhances LLMs by retrieving preprocessed documents from a specific domain (like company data or product manuals), and then integrates this information into the generation process. For example, if you're building a customer service chatbot, RAG can retrieve relevant company documents and use them to generate more accurate, context-aware answers.

Just completed Week 1😊 ... still in development

Spam 😬, you may not even listen to music, but the lyrics in this song are about life. I’ve been listening to it on repeat , it really hits hard. Check it out https://youtu.be/RPpoZYt1QME?si=HzVNItYoxS1W22sV"

📣 Excited to Announce!

WTM Addis and GDG Addis are teaming up with NSK.AI for an incredible AI Bootcamp:

“Intro to AI Agents: From RAG to Deployment”

This FREE, beginner-friendly Bootcamp will help students, developers, and AI enthusiasts build real-world AI apps that can answer questions using their own documents or external knowledge. All hands-on with Langchain and other open-source AI tools!

As a participant, you’ll gain:

✅ Hands-on RAG (Retrieval-Augmented Generation) experience
✅ Practical projects with Langchain & open-source tools
✅ Text & audio AI interactions
✅ A portfolio-ready AI project
✅ Support from a vibrant learning community
✅ Knowledge of vector databases, retrieval strategies, prompt engineering & more

No advanced AI background needed; just curiosity and basic Python skills!

🗓 Starts: 19th July 2025 | 💻 Self-paced | 💰 FREE

Register here 👉 https://forms.gle/1uM8go8yAPpr46KLA to start building real AI apps!

So, week 2 I didn’t touch the IDE project. I started the Play Store app review project instead. It been almost 2 months since I joined the 10Academy AI Kifiya Mastery course. The thing is it is project based learning, and my week 2 project was to do Play Store review analysis for three selected mobile banking apps. Then, in week 6, the project was using RAG to build a customer complaint chatbot. So the idea for this project came to me like by combining week 2 and week 6 project why not owners get actionable insights from users review just by using play Store app id

This is also in progress ... for improvements and my backend is like 👨‍🦽

Starting tomorrow I will post what I gained through this training.

good night ☺️

Always you have been told that work is a curse and labour a misfortune.
But I say to you that when you work you fulfill a part of earth's furthest dream,
assigned to you when that dream was born,
And in keeping yourself with labour you are in truth loving life,
And to love life through labour is to be intimate with life's inmost secret.

from the

The Prophet book

-- Khalil Gibran

Z-score
This is standard normal distribution. The 0 point is the mean of the data and it has standard deviation 1. A data above the average has positive Z-Score and negative for below.

Z-Score is calculated like this

Z = data point - mean of the data
/ Standard deviation

So this indicate how far our data point is from the mean.

The probability of a z-score tells you how likely a value is to appear in a normal distribution and from the image you can see zscore that fall between 3 and -3 have 99.9 probability to be in normal distribution.

Here the use of zscore comes in
Outlier is a data point that is unusual. like we have data of high school students and it is like getting 80 or 5 in age column and the other data is clustered between 15-20.
Outliers affect your model performance.
So the data point with z-score above absolute value of 3 or -3 has 0.1 % chance to be found in normal distribution of the data. So in the another word it is outlier.

#SharingisCaring 😊

I used to remove outlier using percentile before Kifiya Ai
good night 🤌

This GitHub Repo contains pretty much every use case that you can think of with n8n.
https://github.com/Zie619/n8n-workflows.git

The answer to how to approach your twenties

"Everything you do is irrevocable, because time is finite✨ Which means your choices matter.
So you have to choose a fig.
You cannot sit “in the crotch of this fig tree starving to death.”

But choosing one fig does not cause all the others to instantly fall from the tree.
If you realize you’ve chosen the wrong fig—and I mean as soon as you realize, because your twenties are shorter than you think—go back to the tree and pluck another✨
And another
And another
Until you’ve found the right one🤍"
~Caroline

Don't waste your twenties... I think It's the time we plant the seed for the rest of our life.

when ever I try to understand ML algorithm 😁

These are youtube channels I found helpful for ML so far

computerphile he makes the logic behind complex algorithms easy to understand 🤌

Krish helped me to understand ada boost algorithm in minutes. the way he explains 👏

statquest made even the maths simple but not really simple yea I loop over like twice or three times to understand 😁