Implementation of research papers on Deep Learning+ NLP+ CV in Python using Keras, Tensorflow and Scikit Learn.
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Welcome to DeepLearn. This repository contains implementation of following research papers on NLP, CV, ML, and deep learning. Visit my blog for more details - Deeplearn
- Latest Update : Added _deeplearn_utils modules. Check the releases for description of new features.
 Common Representation Learning Using Step-based Correlation Multi-Modal CNN. CV, transfer learning, representation learning. code
 ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs. NLP, deep learning, sentence matching. code
 Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks. NLP, deep learning, CQA. code
 Combining Neural, Statistical and External Features for Fake News Stance Identification. NLP, IR, deep learning. code
 WIKIQA: A Challenge Dataset for Open-Domain Question Answering. NLP, deep learning, CQA. code
 Siamese Recurrent Architectures for Learning Sentence Similarity. NLP, sentence similarity, deep learning. code
 Convolutional Neural Tensor Network Architecture for Community Question Answering. NLP, deep learning, CQA. code
 Improved Representation Learning for Question Answer Matching. NLP, deep learning, CQA. code
 External features for community question answering. NLP, deep learning, CQA. code
 Language Identification and Disambiguation in Indian Mixed-Script. NLP, IR, ML. blog-post || code
The required dependencies are mentioned in requirement.txt. I will also use dl-text modules for preparing the datasets. If you haven’t use it, please do have a quick look at it.
$ pip install -r requirements.txt