12 Data distributions
This chapter covers
- Applying statistical principles of distributions in machine learning
- Understanding the differences between curated and uncurated datasets
- Using population, sampling, and subpopulation distributions
- Applying distribution concepts when training a model
As a data scientist and educator, I get a lot of questions from software engineers on how to improve the accuracy of a model. The five basic answers I give out to increase the accuracy of a model are as follows:
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Increase training time.
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Increase the depth (or width) of the model.
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Add regularization.
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Expand the dataset with data augmentation.
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Increase hyperparameter tuning.
These are the five most likely places to address, and often working ...
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