machine learning with python in this we get into machine learning and how to actually implement machine learning models in python we'll examine what supervised and unsupervised learning meansand how they're different from each other we'll see techniques to prevent overfittingand then look at an interesting example where we implement spam classifier we'll analyze what -means clustering is long the waywith working example that clusters people based on their income and age using scikit-learnwe'll also cover really interesting application of machine learning called decision trees and we'll build working example in python that predict shiring decisions in company finallywe'll walk through the fascinating concepts of ensemble learning and svmswhich are some of my favourite machine learning areasmore specificallywe'll cover the following topicssupervised and unsupervised learning avoiding overfitting by using train/test bayesian methods implementation of an -mail spam classifier with naive bayes concept of -means clustering example of clustering in python entropy and how to measure it concept of decision trees and its example in python what is ensemble learning support vector machine (svmand its example using scikit-learn