Day 2: Supervised Learning Explained + Build Your First ML Model | Learn AI from Scratch 🤖

Day 2 of learning AI from scratch — following the IBM AI Engineering Professional Certificate curriculum. Today we break down Supervised Learning. The concept that powers 80% of all AI in the world. 🤖 What you will learn today: ✅ What Supervised Learning actually means ✅ The bank analogy that makes it click forever ✅ Classification vs Regression explained simply ✅ How GPT-4 was trained (1.8 trillion parameters!) ✅ Build your first ML model in Python (5 lines of code) 🐍 Python code from this video: from sklearn.linear_model import LogisticRegression import numpy as np X = np.array([[1],[2],[3],[4],[5],[6],[7],[8]]) y = np.array([0,0,0,1,1,1,1,1]) model = LogisticRegression() model.fit(X, y) print(model.predict([[5]])) 📺 Watch the full Learn AI from Scratch series: Day 0 — What is AI: [link] Day 1 — Machine Learning: [link] Day 2 — Supervised Learning: [link] 🔔 Subscribe to Decode AI — learning AI from scratch, every single day. #SupervisedLearning #MachineLearning #AI #LearnAI #IBMCertificate #MicrosoftAI #Python #DataScience #AIforBeginners #DecodeAI