Deep learning – what's new and why it matters
The machine learning (ML) algorithms covered in Part 2 work well on a wide variety of important problems, including on text data, as demonstrated in Part 3. They have been less successful, however, in solving central AI problems such as recognizing speech or classifying objects in images. These limitations have motivated the development of DL, and the recent DL breakthroughs have greatly contributed to a resurgence of interest in AI. For a comprehensive introduction that includes and expands on many of the points in this section, see Goodfellow, Bengio, and Courville (2016), or for a much shorter version, see LeCun, Bengio, and Hinton (2015).
In this section, we outline how DL overcomes many of the limitations of other ML algorithms. These limitations particularly constrain performance on high-dimensional and unstructured data that requires sophisticated efforts to extract informative features.
The ML techniques...
