# Dataset requirement for Deep Learning

I am doing research on deep neural networks for prediction. I wanted to know what minimum size of dataset is required for training a deep network. Is there any limitation imposed on how much observations of predictior variables should be there?

• this seems way too broad to be answered with any reasonable precision. training an autoencoder can be done with a few hundred frames, yet training an RL agent can easily take 50 million. – shimao May 20 '18 at 14:49

It largely depends on the problem. On high dimensional datasets like image dataset, it is not uncommon to need $10000$ training points to capture the nuances of data. For Natural Language Processing applications like Seq2Seq, I have trained models with just $3500$ data points.
If the application is more like a Data Analytics problem, where the number of features is typically not greater than $50$, around $1000$ points may be enough. But again, I emphasize that the number of data points needed largely depends on the problem.