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What Are The Best Datasets for Practicing Applied Machine Learning?

What Are The Best Datasets for Practicing Applied Machine Learning?

The best way to get good at applied machine learning is to practice more on different
datasets. If you want to enhance your skills regarding applied machine learning, you must
grab proper details about the best datasets that can help you improve your skills. The more
you practice, the more good results you will grab and have better skills for dealing with
multiple situations. If you want to find more info about the best standard datasets for
practicing, then you can stay focused.

Top 10 Datasets
When an individual opts for improving his skills in applied machine learning, then there is a
total of 10 datasets available that you can consider. Once you learn about all the datasets, it
will be easy for you to connect with them according to your knowledge and understanding.
Here are the significant datasets that can help you to improve your knowledge about applied
machine learning.
1. Iris Flowers Dataset
2. Win Quality Dataset
3. Abalone Dataset
4. Sonar Dataset
5. Wheat Seeds Dataset
6. Boston House Price Dataset
7. Ionosphere Dataset
8. Prima Indian Diabetes Dataset
9. Swedish Auto Insurance Dataset
10. Banknote Dataset


These are the top 10 datasets that you can consider for improving your knowledge about the
applied machine learning. Ensure that you will grab proper details regarding these datasets
so that you won't face any problems while dealing with multiple situations.
Wrap It Up
Different datasets will help you to deal with different problems so try to grab knowledge
about different datasets. Once you paid attention to the information mentioned above, you
can automatically understand the difference between the various problems and the
solutions. Ensure that you will grab proper details about all the datasets if you don't want to
face any problem while dealing with any situation.

Mark Campus

Mark Campus is a content marketer who owns Keenan’s room. A writer by day and a reader by night, he is loath to discuss himself in third person.