April 2018
Beginner to intermediate
500 pages
11h 26m
English
book
Hands-On Machine Learning on Google Cloud Platform
by Giuseppe Ciaburro, V Kishore Ayyadevara, Alexis Perrier, Bryan Fry, Antonio Gulli
Content preview from Hands-On Machine Learning on Google Cloud Platform
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Data splitting
One of the key problems that need to be addressed while working on any machine learning model is: how accurate can this model be once it is implemented in production on a future dataset?
It is not possible to answer this question straight away. However, it is really important to obtain the buy-in from commercial teams that ultimately get benefited from the model build. Dividing the dataset into training and testing datasets comes in handy in such a scenario.
The training dataset is the data that is used to build the model. The testing dataset is the dataset that is not seen by the model; that is, the data points are not used in building the model. Essentially, one can think of the testing dataset as the dataset that is likely ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.