# time series prediction training on multiple lags using tensorflow 2

I am just studying tensorflow 2. Here is where I learned time series training on multiple lags using LSTM: https://machinelearningmastery.com/multivariate-time-series-forecasting-lstms-keras/

In this example, time series should be turned into classification format to use LSTM. For example, if the original data looks like:

date   a1   a2   target
1      1    2      0.2
2      2    3      0.3
3      3    4      0.5
...


Then, for lag=1, the data should be turned to:

       time t-1               time t-1
date   a1   a2   target    a1   a2   target
1      1    2      0.2     2    3      0.3
2      2    3      0.3     3    4      0.5
...


So if there is multiple lag, then the above data frame will include a lot of columns, corresponding to multiple time points.

This seems complex for me. But I am new to LSTM and tensorflow, I do not know if there is some other way to do this?