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3 Prerequisites and Notation

If you have taken a Machine Learning course such as my machine learning MOOC on
Coursera, or if you have experience applying supervised learning, you will be able to
understand this text.

I assume you are familiar with ​supervised learning​: learning a function that maps from x

to y, using labeled training examples (x,y). Supervised learning algorithms include linear
regression, logistic regression, and neural networks. There are many forms of machine
learning, but the majority of Machine Learning’s practical value today comes from
supervised learning.

I will frequently refer to neural networks (also known as “deep learning”). You’ll only need a
basic understanding of what they are to follow this text.

If you are not familiar with the concepts mentioned here, watch the first three weeks of
videos in the Machine Learning course on Coursera at ​http://ml-class.org

Page 9 Machine Learning Yearning-Draft Andrew Ng