How can I train a neural network with information about academic courses (mostly text as input, 1 numeric) to classify whether the course is future proof?
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Christiaan Teeuwen on 17 Sep 2018
Edited: Christiaan Teeuwen on 24 Sep 2018
The test database that I have is a has 6 input variables (5 in text, 1 numeric) and one (0 or 1) output variable saved in a table. These 6 input variables describe content of academic courses. The name, description, learning outcomes, level, #credits and department. In a training set of 93 courses I identified 20 courses that are FutureProof. This is a time intensive task. The rest of the database consist of ±2000 courses.
How can I train a neural network (if this is the right choice) on this training set to identify which of the other ±1900 courses can be classified as future proof and which cannot?
Thanks a lot in advance!
Vishal Bhutani on 21 Sep 2018
By my understanding, you want to train a neural network which is having input data of both type numerical as well as nominal variables. The link attached will refer to the same issue you are facing:
Hope it helps.
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