Best Results for Standard Machine Learning Datasets

Last Updated on August 28, 2020

It is important that beginner machine learning practitioners practice on small real-world datasets.

So-called standard machine learning datasets contain actual observations, fit into memory, and are well studied and well understood. As such, they can be used by beginner practitioners to quickly test, explore, and practice data preparation and modeling techniques.

A practitioner can confirm whether they have the data skills required to achieve a good result on a standard machine learning dataset. A good result is a result that is above the 80th or 90th percentile result of what may be technically possible for a given dataset.

The skills developed by practitioners on standard machine learning datasets can provide the foundation for tackling larger, more challenging projects.

In this post, you will discover standard machine learning datasets for classification and regression and the baseline and good results that one may expect to achieve on each.

After reading this post, you will know:

• The importance of standard machine learning datasets.
• How to systematically evaluate a model on a standard machine learning dataset.
• Standard datasets for classification and regression and the baseline and good performance expected on each.

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