I've used keras a bit for deep learning recently. In general it is an excellent tool, but I know there are limitations in using a higher-level tool. In trying to implement an initial model in tensorflow, I found that you have to think about fundamentals of data flow and building computation graphs -- as opposed to machine learning a la sklearn
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I've been working on text classification recently. I've found keras to be a quite good high-level language and great for learning different neural network architectures. In this notebook I will examine Tweet classification using CNN and LSTM model architechtures. While CNNs are widely used in Computer Vision, I saw a paper
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