Application of Keras neural network in the era of big data

Abstract

Abstract The experiment uses crawler tools to obtain data, and the data is preprocessed to find missing values and eliminate invalid data, meanwhile, the model is constructed by information entropy and ID3 algorithm so as to select the desired amount of features, and then basic modeling and data filtering is performed to train and evaluate the model for the first time, finally, in order to get a more ideal model, this experiment The optimal model is obtained by changing the number of hidden layers and neurons of the neural network to build a high-level neural network API neural network model written by pure python - Keras neural network model. The results show that when the model defines a 2-layer neural network and the number of neurons in the hidden layer is fourteen, the accuracy of the model is the highest, and the accuracy of the test set is as high as ninety-one percent.