I have a dataset of which has 30M rows each like [current_jobtitles, nextjobtitles].
[['junior software programmer', 'senior software programmer'], ['senior software programmer', 'lead software programmer'], ['sales associate', 'regional sales associate']]
I want to build a deep learning model to predict the nextjobtitle when a currenttitle is given. Are there any ways that I could acheieve this using some deep learning model? if yes, what kind of model ?
Can we use any of the text generation models for this scenario ? I have seen some examples, but I cannot relate to my solution for the problem. Any suggestions please ..!
I have sequences of jobtitles in each row.
[['junior programmer', 'senior programmer', 'lead programmer'], ['sales associate', 'sales regional associate', 'sales manager'], ['chairman', 'ceo'], ['associate', 'intern', 'junior', 'student']]
for the orginal data (in update) i have modifed data as above (before update) by just taking the nextjob title. Can I train model with the original sequence data to predict the next jobtitle? ** - all the rows will be of different lengths.