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If the dataset is large does it mean that the model size will also be large?

Md Faysal Ahmed Akash
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for example our real world data is function y = ax + b

dataset is all data point on this line

model is our mathematical representation for representing these data

model size is number of parameter we use for representation

now the model size is related to a real world function we want to representing.

we can create a huge dataset for line ax + b but the model of this function only need two parameters a and b and if we have only two point of this line we can create model

real world data are not simple as a line but if we have some model with same result model with least number of parameter is beast one.

The training dataset size depends on the complexity of our model

amin saffar
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  • Thanks for response. For example, let's say i have 2 dataset of image one containing 1000 48*48 pixels grayscale image, and the other one containing 500. Now if i train a neural network with only one hidden layer, will the resultant models vary in size? @amin saffar – Md Faysal Ahmed Akash May 31 '20 at 21:22