December 2018
Intermediate to advanced
274 pages
7h 46m
English
Content preview from Machine Learning for Mobile
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Supervised learning
Supervised learning is a type of learning where the model is fed with enough information and knowledge and closely supervised to learn, so that, based on the learning it has done, it can predict the outcome for a new dataset.
Here, the model is trained in supervision mode, similar to supervision by teachers, where we feed the model with enough training data containing the input/predictors and train it and show the correct answers or output. So, based on this, it learns and will become capable of predicting the output for unseen data that may come in the future.
A classic example of this would be the standard Iris dataset. The Iris dataset consists of three species of iris and for each species, the sepal length, sepal width, ...
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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.