How to Split Up Data for Machine Learning

70 to 80% of the time that you will spend as a data science or machine learning, or just in general, that 70 to 80%, usually it's like 80%. You can be spending most of your time doing this data preparation or collecting it, aggregating and augmenting it. In addition to just cleaning the data and getting it into the right format, we may need to split it up into different parts. This is an aspect of what's called data splitting. And another area that we can focus on is data transformation.