March 2018
Intermediate to advanced
1396 pages
42h 14m
English
Until now, we have been discussing deep neural networks and some of their applications in robotics and image processing. Apart from neural networks, there are a lot of models available to classify data and predict using them.
Generally, in machine learning, we can teach the model using supervised or unsupervised learning. In supervised learning, we training the model against a dataset, but in unsupervised, it discover groups of related observations called clusters instead.
There are lot of libraries available for working with other machine learning algorithms. We'll look at one such library called scikit-learn; we can play with most of the standard machine learning algorithms and implement our own application using ...