Logistic Regression in Python | Mastering Deep Learning

Logistic Regression in Python | Visualizing Decision Boundaries and Optimization

Dive into the world of binary classification with our practical session on logistic regression, where we craft and visualize the decision boundary using a synthetic dataset. This hands-on tutorial is ideal for learners who want to see logistic regression in action, illustrating how the log loss function is minimized through gradient descent.

This video is a crucial part of our series "On Deep Learning by Ian Goodfellow et al: Deep Learning Essentials." Here, we break down the logistic regression model, explaining the significance of the sigmoid function's output as a probability, which underpins many binary classification tasks. Join us as we detail the process, step-by-step, demonstrating how logistic regression delineates classes by optimizing the decision boundary.

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[samuelbenhur]

Thank you for your video on face recognition with mtcnn, facenet and svm. It was really helpful for my Grad degree project.