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  How to Build a Data Analyst Portfolio With ZERO Experience (The Part Everyone Avoids) Let’s clear something up immediately: If you’re learning data analytics and don’t have a portfolio, you are invisible to recruiters. Courses won’t save you. Certificates won’t save you. And no, “I’m still learning” is not an excuse anymore. Most beginners fail here — not because they’re stupid, but because they’re confused about what actually counts as experience . First: Stop Waiting for “Real” Experience Here’s the uncomfortable truth: Companies don’t care where your experience came from. They care what you can do . If you’re waiting for: an internship a first job permission to start You’ve already lost months for no reason. A portfolio project is experience if: it solves a real problem it uses real data you can explain your thinking That’s it. No magic. The Biggest Portfolio Mistake Beginners Make They build toy projects . Examples: random Kaggle noteboo...

  Is Data Analytics Worth It for Non-Tech People in 2026? Everyone keeps saying “learn data analytics” like it’s a shortcut to money. It’s not. For some people, data analytics is a solid career move. For others, it’s a frustrating waste of time. If you’re from a non-tech background and thinking about data analytics mainly for better income , this post will tell you the truth most blogs avoid. What Is Data Analytics ? Data analytics means: looking at data understanding what it shows helping businesses make better decisions You are not building apps or complex software. You are answering questions like: Why did sales drop? Which product performs best? Where is the problem? If you like understanding patterns and solving problems, this matters more than being “good at tech.” Is Data Analytics Still Useful in 2026? Yes — because companies will always need people who can understand data . Businesses are collecting more data every year. But data alone is ...

🎭 Building a Robust Real-Time Emotion Detection System Using Ensemble Learning   🔗 GitHub Repository: https://github.com/KToppo/Emotion-Detection-ML Human emotion recognition has emerged as a powerful tool in modern AI applications—ranging from digital well-being solutions to marketing analytics and interactive systems. In this project, I built a Real-Time Emotion Detection System that uses a camera feed or an image URL to classify a person’s facial expression into one of several emotion categories. The complete project — including code, models, pipelines, and demo — is available on GitHub: 👉 https://github.com/KToppo/Emotion-Detection-ML This blog documents the entire journey — from data preprocessing to final deployment — and highlights the experiments, improvements, and insights gained along the way. 📂 Project Structure Here is the complete directory structure: ├── models/ │ ├── labels_1.pkl │ ├── labels_2.pkl │ ├── labels_3.pkl │ ├── M1SMOTE_boost.png │ ├── M1...