unsupervised learning in the machine learning ecosystem most of human and animal learning is unsupervised learning if intelligence was cakeunsupervised learning would be the cakesupervised learning would be the icing on the cakeand reinforcement learning would be the cherry on the cake we know how to make the icing and the cherrybut we don' know how to make the cake we need to solve the unsupervised learning problem before we can even think of getting to true ai --yann lecun in this we will explore the difference between rules-based system and machine learningthe difference between supervised learning and unsupervised learningand the relative strengths and weaknesses of each we will also cover many popular supervised learning algorithms and unsupervised learning algorithms and briefly examine how semisupervised learning and reinforcement learning fit into the mix basic machine learning terminology before we delve into the different types of machine learninglet' take look at simple and commonly used machine learning example to help make the concepts we introduce tangiblethe email spam filter we need to build simple program that takes in emails and correctly classifies them as either "spamor "not spam this is straightforward classification problem here' bit of machine learning terminology as refresherthe input variables into this problem are the text of the emails these input variables are also known as features or predictors or independent variables the output variable--what we are trying