Machine learning technology is now ubiquitous, and its societal impact is exploding, from self-driving cars to the targeted ad campaigns that may have swung the 2016 election. The work of Ludwig Wittgenstein, one of the 20th century's leading philosophers, has a lot to tell us about the nature and limits of these technologies. This course provides a concise introduction to both machine learning and Wittgenstein's thought, and investigates what these two subjects have to say about each other. The two-hour class will consist of three parts. The first part will be a brief introduction to key concepts in machine learning such as supervised and unsupervised learning, classification and regression, clustering, support vector machines, neural nets, and applications. The second part will introduce Wittgenstein's ideas about the philosophy of mind and language, with a special focus on the private language argument and the indeterminacy of meaning. In the final part of the class, we will reinvestigate notions of machine learning from the perspective of Wittgensteinian philosophy by trying to answer questions such as, "What does it really mean to 'learn' a rule?" and "How can we know when we have successfully recognized a pattern?"