Based on the “Machine Learning ” crash course from Google for Developers: https://developers.google.com/machine-learning/crash-course
In this episode, we dive into the world of classification in machine learning—exploring how models make decisions and how we evaluate their performance. You'll learn what a confusion matrix is, how thresholds affect predictions, and what metrics like accuracy, precision, recall, and F1 score really mean in practice. Whether you're new to ML or brushing up on the fundamentals, this episode will give you the clarity you need to confidently interpret model results.
Disclaimer: This podcast is generated using an AI avatar voice. At times, you may notice overlapping sentences or background noise. That said, all content is directly based on the official course material to ensure accuracy and alignment with the original learning experience.