November 2017
Beginner
286 pages
8h 13m
English
book
Statistics for Data Science
by James C. Mott, Rajprasath Subramanian, Shaikh Salamatullah, James D. Miller, Vijayakumar Ramdoss
Content preview from Statistics for Data Science
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Weak to strong
Better than random guessing is fundamentally the one and only prerequisite for a weak learner. So, as long as an algorithm or model can consistently beat random guessing, applying a boosting algorithm will be able to increase the accuracy of the model's predictions (its performance) and consequently convert the model from being a weak learner to a strong learner.
Take note, data scientists agree that increasing a model's predictive ability or performance even to ever so slightly better than random guessing results means success.
When a data scientist considers the options for improving the performance of a model (or converting a weak learner to a strong learner), numerous factors need to be considered.
These factors include ...
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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.