I want to create a neural network and train it on some data, however I want to be able to create a new model without retraining it from the start.

An example, I have 1000 data points in my training data

model - trained on 0-99model - trained on 1-100model - trained on 2-101and so forth

So I'm wondering if I can use the first model to train the second model, essentially forgetting the first data point.

You can view it as a sliding window over the 1000 data points, sliding one data point to the right for each new model.

Does it make sense?Is there any easy way to solve this problem?