A Layman guide to moving from Keras to Pytorch
Recently I started up with a competition on kaggle on text classification, and as a part of the competition, I had to somehow move to Pytorch to get deterministic results. Now I have always worked with Keras in the past and it has given me pretty good results, but somehow I got to know that the CuDNNGRU/CuDNNLSTM layers in keras are not deterministic, even after setting the seeds. So Pytorch did come to rescue. And am I glad that I moved.
As a side note: If you want to know more about NLP, I would like to recommend this awesome Natural Language Processing Specialization . You can start for free with the 7-day Free Trial. This course covers a wide range of tasks in Natural Language Processing from basic to advanced: sentiment analysis, summarization, dialogue state tracking, to name a few.
Also take a look at my other post: Text Preprocessing Methods for Deep Learning , which talks about different preprocessing techniques you can use for your NLP task and What Kagglers are using for Text…
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