Machine Learning 101

With all of the attention on machine learning, many are seeking a better understanding of this hot topic and the benefits that it could provide to their organizations. Therefore, this course attempts to demystify the key concepts that drive machine learning. No experience in Machine Learning is needed.

Machine learning – as well as deep learning, natural language processing and cognitive computing is defined as a subset of artificial intelligence that, when given data, a machine can learn/apply it. Such technological feats are driving innovations in identifying images, personalizing marketing campaigns, genomics, and navigating the self-driving car.

What you should know before taking this course

Intro-level algebra. You should be comfortable with variables and coefficients, linear equations, graphs of functions, and histograms. (Familiarity with more advanced math concepts such as logarithms and derivatives is helpful, but not required.)

Proficiency in programming basics, and some experience coding in Python. Programming exercises in Machine Learning Crash Course are coded in Python using TensorFlow. No prior experience with TensorFlow is required, but you should feel comfortable reading and writing Python code that contains basic programming constructs, such as function definitions/invocations, lists and dicts, loops, and conditional expressions.