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I'm a newbie to python, i need to complete a project on IMDB Review sentiment analysis. I did not quiet understand how to train the imdb dataset aclImdb_v1.tar to a model. Please show me how to train a model from this dataset.

Below is the method I need to implement for my project.

Text Reviews -> Embedded Layer -> Word vector generation -> CNN -> Feature Maps -> LSTM -> Classification layer

The result I expect is to find if a review taken as input is either positive or negative. Please help me out and pardon my unknowledgeable words, if any..

AruN
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  • This sounds like a university course project? I'd suggest asking the teacher what books/etc. you should read to know how to tackle it. Then (once you've read them), come back with more specific questions, showing what you've done, what error you get, or what results you get, etc. – Darren Cook Feb 12 '19 at 16:44

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If the size of your dataset is quite large you can easily employ Deep Learning to complete your project. First, you need to create a pipeline to convert your data into well representable form, and then feed into the model.

And do not worry about computational costs if you are writing in TensorFlow, the Google Cloud TPU offers free service on Google Colab.

  • Thank you for your response sir, Is there any example that i can follow to to convert the dataset to a representable form? – AruN Feb 12 '19 at 10:06