Data analysis and deep learning will be used to create a model ,based on the given dataset , which will help identify the total number of buses required in order to accomodate the traffic in the future. The dataset used has been imported from kaggle. Given below is the link for the same. Adealide Transport Data The data is of the metropolitan city Adealide. The data of this module is relatively simplified as it does not contain any missing values. We will import the dataset using the required libraries and then perform EDA , in order to understand which of the given factors are playing a major role in determiningthe load,such that the deep learning algorithm can perform to its best of abilities. The dataset will be divided into test set and training set.After that, the LSTM deep learning model will be used to fit on the dataset. Predictions will be made.
tarushi98/PredictingBusesRequiredLSTM
Predicting Total Number of Buses Required at A given interval of time depending on past history of a particular area.
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