Are there any ways to create a deep multilayer perceptron model that is capable of making accurate regression predictions based on the training done using around 1000 unique data?
I'm currently working on a Kaggle challenge for predicting the amount Followers gained using the top 1000 streamers on Twitch 2020 dataset.
- The X value would be every columns excluding Followers gained;
- The y value would be the amount of Followers gained - the model will make predictions regarding this.
In general, the data values for the amount of followers gained contain around 6 to 7 digits; currently my RMSE loss value is almost near to become 5 digits, yet still 6.
There are limited quantity of data; I'm aiming for a 5 digit RMSE value.