ahmedbesbes/character-based-cnn
Implementation of character based convolutional neural network
This project offers a character-level convolutional neural network designed for text classification. It takes raw text data, such as customer reviews or social media posts, and classifies it into predefined categories, like positive or negative sentiment. This tool is ideal for data scientists, natural language processing engineers, or researchers working with text data who need an efficient way to categorize text.
262 stars. No commits in the last 6 months.
Use this if you need to classify large volumes of text quickly and accurately, without extensive preprocessing, and want a model that can handle misspelled words or new terms.
Not ideal if your primary goal is to understand the semantic meaning or complex linguistic relationships within text, as this model focuses on character patterns rather than word semantics.
Stars
262
Forks
54
Language
Python
License
MIT
Category
Last pushed
Apr 28, 2021
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/ahmedbesbes/character-based-cnn"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Higher-rated alternatives
carpedm20/lstm-char-cnn-tensorflow
in progress
ilivans/tf-rnn-attention
Tensorflow implementation of attention mechanism for text classification tasks.
AlexGidiotis/Document-Classifier-LSTM
A bidirectional LSTM with attention for multiclass/multilabel text classification.
NonvolatileMemory/AAAI_2019_EXAM
Official implementation of "Explicit Interaction Model towards Text Classification"
vietnh1009/Character-level-cnn-pytorch
Character-level CNN for text classification