AI in general and Machine Learning in particular, has been the subject of frenzied media hype in the past few years. Algorithmic improvements, uber-powerful hardware, and availability of massive datasets has kickstarted a process of massive resurgence of research in the field. Industry investment in Machine Learning and Data Science has reached levels never seen before. A student or software practitioner starting off in the field can have a hard time knowing where to start and how to keep up with this fast-changing landscape.
We’ll take a top-down approach to exploring the field of Machine Learning. Along the way, we’ll demystify core concepts and bust some jargon. We’ll develop intuitions on widely-used Machine Learning models and explore software libraries that map to these techniques. We’ll do hands-on coding to see some of these approaches in action.