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A sequence to sequence prediction for developing a classification system is of very much required in developing applications. Standard approaches for developing applications won't help in providing accuracy. Hence, as an example let's take an IMDB movie review dataset and create some benchmarks by using RNN, RNN with LSTM and drop out rate, RNN with CNN, and RNN with CNN plus drop out rate to make a composite sequence to sequence classification work. We can compare the model accuracy as well.
The goal of this tensorflow project is to identify hand-written digits using a trained model using the MNIST dataset. The MNIST dataset contains a large number of hand written digits and corresponding label (correct digit)
In this data science project, we are going to work on video recognization data and a robust level of image recognization MNIST data.
In this deep learning project, we are going to predict which team will win the NCAA basketball tournament of coming 2017 based on past historical data.