Overview
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore a beginner-friendly introduction to machine learning and spam detection in this EuroPython conference talk. Learn key concepts of supervised learning and classifiers as you build a basic email spam filter using Python and the Naive Bayes algorithm. Discover how to define machine learning problems, understand the Bayesian approach, and implement a "bag of words" model for text classification. Gain insights into performance measurement, false positives, and ways to improve your spam detection model. Walk through the process of training a classifier using labeled examples and applying it to new data. Perfect for those new to programming or Python who want to demystify machine learning concepts and gain practical experience in building a common type of classifier.
Syllabus
Intro
About Lorena
Todays questions
What is machine learning
Defining machine learning
Learning from experience
Learning from pain
Learning from memories
What does experience mean
Naive Bayes
Bayes Theorem
Assumptions
Bayesian classifiers
Why naive Bayes
How to detect spam
What are we going to use
Bag of Words
Classification
Performance Measurement
False Positives
Side Effects
Improving Performance
Recommended Resources
Conclusion
Taught by
EuroPython Conference