ML Foundations – Linear & Logistic Regression Theory

📊 Live Session: Machine Learning Basics - Linear and Logistic Regression Theory Linear & Logistic Regression Theory 📅 Date: October 6 ⏰ Time: 9 PM (Dubai time) 📍 Live on DevMENA's YouTube channel: https://www.youtube.com/live/lMIFuW-9c5o?si=12kkwYjclApX_ElI 🎙️ Speaker: Mustafa Gamal Ghoneim - Junior Computer Vision Engineer Welcome back to the Machine Learning Basics series! In this session, we dive deep into Linear & Logistic Regression Theory — two of the most important techniques in the field of machine learning. 🎯 What you'll learn: Linear Regression: 🔹 Simple Regression vs. Multiple Regression 🔹 Key assumptions and Ordinary Least Squares (OLS) estimation 🔹 Real-world examples Logistic Regression: 🔹 Conditional Probability, odds, and log-odds 🔹 The logistic function and logistic regression algorithm (MLE) 🔹 When and why to use it? ✨ Plus: A comparison between the two models, their strengths, weaknesses, and use cases.