I just completed Module 1: Introduction to Machine Learning from ML Zoomcamp 2026 🎉
This module covered:
🔹 Difference between ML and rule-based systems
🔹 What supervised machine learning is
🔹 CRISP-DM: a framework for structuring ML projects
🔹 The model selection step
🔹 Setting up the environment (Python, Jupyter, etc.)
🔹 Quick refreshers on NumPy, linear algebra, and Pandas
✨ My key takeaway: Practice. Practice. Practice.
🤔 Something I found interesting: How linear algebra is challenging!
➡️ Next step → Module 2: How to gain hands-on, supervised learning
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