Different Models of Text Classification with Tensorflow

Models of Text classification are used to categorize text into ordered groupings. A model analyzes the text, and then the appropriate tags are added based on the content. Machine learning models that can add classification tags automatically are known as classifiers.

Example of Text Classification

• Sentiment Analysis
• Language Detection
• Product Classification
• Topic Classification

Text Classification Models with Tensorflow

Implemented Models:

• Word-level CNN
• Character-level CNN
• Very Deep CNN
• RCNN
• Attention-Based Bidirectional RNN
• Word-level Bidirectional RNN

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Prerequisites Requirement

• Python3
• Tensorflow

How Train and Test Model

For Train Model

$ python train.py --model="<MODEL>"

For Test Model

$ python test.py --model="<TRAINED_MODEL>"