codeit provides a number of different tools that use AI (Artificial intelligence) to perform coding tasks so that you can reduce or minimise the amount of coding that needs to be done by a human. One of these methods used is Machine Learning.
What is Machine Learning?
Codeit learns from the coded examples you provide and uses this learning to autocode. This extends the autocoding beyond text or pattern matching, to autocode based on semantic theme.
For example, coding examples like:
"It helps me relax"
"I find it calming"
will enable to Codeit to autocode verbatims like:
"This is great for chilling out"
"It is great for unwinding"
even though these phrases are completely textually dissimilar.
Machine Learning can be run after a first wave or initial batch of coding has been completed - as machine learning needs to learn from how the initial batch of coding was completed by the human coders. As more and more coding is completed, the machine learning can apply more coding. Note that if you have any coding that had already been completed before you started using codeit, you can also import that previously coded data into your project so that the machine learning can be applied from the start.
How can this be set up in codeit?
Watch the video below to learn how to set up and apply Machine Learning in codeit. Also refer to the Complete & Partial coding guide which explains how codeit allows you to specify the level of "completeness" required before a verbatim can be autocoded.
You can find a guide to the symbols used in the verbatim screen for the different AI functions here.