Inspiration

Learning the behavior of LSTM Networks for time series prediction

What it does

Create a LSTM network to predict bakery sales

How we built it

We built it with tensorflow keras and pycharm

Challenges we ran into

Missing datas, variations in the data format, LSTM categorizing, data stationarity

Accomplishments that we're proud of

We managed to prepare the data and were able to train the network.

What we learned

We learned that the preporcessing takes a lot of effort and we have split the dataset into time windows for better training results.

What's next for Time Series Prediction for Bakery Turnovers

Optimize the Dataset input variables (min-max, stationarity, etc.) and the LSTM Network. Furthermore we have to check, if other network types like VAR or transformer networks can improve our predictions.

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