Different between the operators in modelling -> predictive
maurits_freriks
Member Posts: 28 
Contributor I
Hi all,
For buidling a predictive process of the flow of tomorrow I only use the flow in the past. So this is a regression problem, with only the variable Flow per day. I devide this with windowing in to 5 days. D-1, D-2, D-3, D-4 and D-5. And i would to apply different predictive models.
It's really hard to understand for me what the difference between Neural network, Suport Vector Machine and Deeplearning is. But therefore I need maybe to understand each model individualy. I searched on the internet but I could not find a proper and easy way to understand the different models. Therefor I ask the question here kindly if you guys could explain briefly the models with concerning my model:
- Neural Network.
- Suport vector machine.
- Deep learning.
Answers
hi @maurits_freriks - have you checked out our YouTube channel?
Deep Learning: https://www.youtube.com/watch?v=rJCU8ODRwyg and https://www.youtube.com/watch?v=JLuekxdQkMM
SVMs: https://www.youtube.com/watch?v=YsiWisFFruY and https://youtu.be/woEwY0Zi6X4
Scott
@sgenzer
Yes but it is hard for me to understand because we only have the "flow per day" and not two totally different variables as Length and weight or something. I don't get it how you could devide the flow per day into multiple classes, refering to the SVM (blue and red dots)