December 2018
Intermediate to advanced
158 pages
3h 58m
English
One of the main drawbacks to supervised learning is that it requires data that is accurately labeled. Most real-world data consists of unlabeled and unstructured data and this is the major challenge to machine learning and the broader endeavor of artificial intelligence. Unsupervised learning plays an important role in finding structure in unstructured data. The division between supervised and unsupervised learning is not absolute. Many unsupervised algorithms are used to together with supervised learning; for example, where data is only partially labeled or when we are trying to find the most important features of a deep learning model.
Read now
Unlock full access