Python Programming Lecture Series- Part 18 (Logistic Regression as a Binary Classifier) скачать в хорошем качестве

Python Programming Lecture Series- Part 18 (Logistic Regression as a Binary Classifier)

Welcome to Part 18 of our Python Programming Series! In this video, we delve into the fascinating world of Logistic Regression and its essential role as a binary classifier. I am using Google Colab for our demo session, making it accessible and easy for everyone to follow along. In this episode, I'll guide you through the process of creating a Logistic Regression model and training it using the powerful scikit-learn library. To make things hands-on and practical, I have generated a small binary classification dataset with 100 samples using numpy functions. But that's not all! I will also address a critical question: Why can't we use linear regression for binary classification? Understanding this fundamental concept is crucial, and I will provide a clear explanation to ensure you grasp the key differences between these two techniques. If you're new to Logistic Regression or need a refresher, don't worry! I kindly request you to check out Part 17 of our series, where I introduced Logistic Regression and discussed the essential Sigmoid function in detail. It's the perfect prelude to this informative session. Whether you're a beginner or an experienced Python programmer, this video has something valuable for you.