# training neural net with multiple sets of time-series data

I have the following data

($x^1_i$, $y^1_i$) for $i=1,2,...N_1$

($x^2_i$, $y^2_i$) for $i=1,2,...N_2$

...

($x^m_i$, $y^m_i$) for $i=1,2,...N_m$

Is it possible to train a neural net to produce some $y_k$ where $k<=min(N)$ given a input ${x_1, x_2, ..., x_{k-1}}$?

If so any suggestion of documentation/ library I can look at (preferably python)?