1. What is deep learning

 Previous machine-learning techniques—shallow learning—only involved transforming the input data into one or two successive representation spaces, usually via simple transformations such as high-dimensional non-linear projections (SVMs) or decision trees. But the refined representations required by complex problems generally can’t be attained by such techniques.  
they had to manually engineer good layers of representations for their data. This is called feature engineering. 
Increased computational expense? => improved hardware, GPU computing, TPU
and by the rise of user-friendly libraries such as Keras, which makes deep learning as easy as manipulating LEGO bricks.
也没有这么简单吧😂
7/31/2019 chapter 1