jiegzhan/multi-class-text-classification-cnn
A convolutional neural network with word embeddings trained on TensorFlow/Keras to classify consumer finance complaints into 11 categories.
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This repository implements a multi-class text classification model using a Convolutional Neural Network and word embeddings. The model is built with TensorFlow 2 and Keras, trained on the Kaggle Consumer Finance Complaints dataset to predict product categories from complaint narratives. The workflow includes training scripts that produce a best model checkpoint and prediction scripts for inference on new data.
Frequently asked
- What is jiegzhan/multi-class-text-classification-cnn?
- A convolutional neural network with word embeddings trained on TensorFlow/Keras to classify consumer finance complaints into 11 categories.
- Is multi-class-text-classification-cnn open source?
- Yes — jiegzhan/multi-class-text-classification-cnn is open source, released under the Apache-2.0 license.
- What language is multi-class-text-classification-cnn written in?
- jiegzhan/multi-class-text-classification-cnn is primarily written in Python.
- How popular is multi-class-text-classification-cnn?
- jiegzhan/multi-class-text-classification-cnn has 425 stars on GitHub.
- Where can I find multi-class-text-classification-cnn?
- jiegzhan/multi-class-text-classification-cnn is on GitHub at https://github.com/jiegzhan/multi-class-text-classification-cnn.