May 2020
Intermediate to advanced
530 pages
17h 8m
English
Content preview from Hands-On Machine Learning with C++
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Grid search
The main idea behind the grid search approach is to create a grid of the most reasonable hyperparameter values. The grid is used to generate a reasonable number of distinct parameter sets quickly. We should have some prior knowledge about the task domain to initialize the minimum and maximum values for grid generation, or we can initialize the grid with some reasonable broad ranges. However, if the chosen ranges are too broad, the process of searching for parameters can take a long time and will require a significant amount of computational resources.
At each step, the grid search algorithm chooses a set of hyperparameter values and trains a model. After that, the training step algorithm uses the K-fold cross-validation technique ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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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.