One of the essential things in machine learning is the data that we use for training. We can gather training data from the processes we work with, or we can take already prepared training data from third-party sources. In any case, we have to store training data in a file format that should satisfy our development requirements. These requirements depend on the task we solve, as well as the data-gathering process. Sometimes, we need to transform data stored in one format to another to satisfy our needs. Examples of such needs are as follows:
- Increasing human readability to ease communication with engineers
- The existence of compression possibility to allow data to occupy less space on secondary storage
- The use of data in the binary form to speed up the parsing process
- Supporting the complex relations between different parts of data to make precise mirroring of a...
