Jan. 22, 2022, 11:46 p.m. | /u/teacupip

Deep Learning www.reddit.com

Hi!

I'm trying to build a recommendation model but my model learns very well in train but in test the results decrease (yeah, overfitting).

My number of parameters were much higher than my number of data so I tried to do data augmentation but it didn't work. I tried to add L2 regularization, dropout and batchNorm but without any success.

Do you have any suggestions? What could explain this overfitting? How to counteract it?

I take all tracks to try. …

deeplearning overfitting

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Praktikum im Bereich eMobility / Charging Solutions - Data Analysis

@ Bosch Group | Stuttgart, Germany

Business Data Analyst

@ PartnerRe | Toronto, ON, Canada

Machine Learning/DevOps Engineer II

@ Extend | Remote, United States

Business Intelligence Developer, Marketing team (Bangkok based, relocation provided)

@ Agoda | Bangkok (Central World)