Naive Bayes Introduction
Naive Bayes is a fundamental machine learning algorithm. Despite its simplicity, Naive Bayes is one of the useful and commonly used classification algorithms. This talk will cover how the algorithm works and implement the Naive Bayes algorithm from scratch. Common use cases and practical examples will be shown. This talk is designed for beginners who have an interest in machine learning, prior exposure to probability and Python would be helpful to get the most out of it. By the end, you should have a deeper understanding of Naive Bayes.
Slides and code are here.
About Me
Brian Spiering is Data Science Instructor at Metis. He teaches humans the languages of computers (primarily Python) and teaches computers the languages of humans (through Natural Language Processing and Artificial Intelligence). He is active in global tech community through volunteering and mentoring.