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Long-short Term Memory (LSTM) is a kind of recurrent neural network (RNN) that uses a special kind of cell that is able to memorise information by having gateways that pass through different cells. This is critical for long sequence data as a simple RNN without any special cells like LSTM or GRU suffers from the vanishing gradient problem. Create the convolutional base. The 6 lines of code below define the convolutional base using a common pattern: a stack of Conv2D and MaxPooling2D layers. As input, a CNN takes tensors of shape (image_height, image_width, color_channels), ignoring the batch size. If you are new to these dimensions, color_channels refers to (R,G,B). On the Phishtank dataset, the DNN and BiLSTM algorithm-based model provided 99.21% accuracy, 0.9934 AUC, and 0.9941 F1-score. The DNN-BiLSTM model is followed by the DNN-LSTM hybrid model with a 98.62% accuracy in the Ebbu2017 dataset and a 98.98% accuracy in the PhishTank dataset.