chiragjn/deep-char-cnn-lstm
Deep Character CNN LSTM Encoder with Classification and Similarity Models
This is a low-level software component for developers building advanced text analysis systems. It processes raw text inputs to generate rich numerical representations (embeddings) of words, taking into account both character-level and word-level features. Data scientists and machine learning engineers can use this to create custom models for tasks like text classification or identifying similar text passages.
No commits in the last 6 months.
Use this if you are a machine learning engineer or data scientist looking to implement a custom character-aware neural network for text processing within a Python/Keras environment.
Not ideal if you are looking for a ready-to-use application or a high-level library for off-the-shelf text analysis; this requires significant development work to be functional.
Stars
20
Forks
6
Language
Python
License
MIT
Category
Last pushed
Feb 15, 2018
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/chiragjn/deep-char-cnn-lstm"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
codelion/adaptive-classifier
A flexible, adaptive classification system for dynamic text classification
jiegzhan/multi-class-text-classification-cnn-rnn
Classify Kaggle San Francisco Crime Description into 39 classes. Build the model with CNN, RNN...
jiegzhan/multi-class-text-classification-cnn
Classify Kaggle Consumer Finance Complaints into 11 classes. Build the model with CNN...
cbaziotis/datastories-semeval2017-task4
Deep-learning model presented in "DataStories at SemEval-2017 Task 4: Deep LSTM with Attention...
iamaziz/ar-embeddings
Sentiment Analysis for Arabic Text (tweets, reviews, and standard Arabic) using word2vec