Scripts for an upcoming blog "Extractive vs. Abstractive Summarization" for RaRe Technologies.
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Updated
Apr 7, 2017 - Jupyter Notebook
Scripts for an upcoming blog "Extractive vs. Abstractive Summarization" for RaRe Technologies.
Tensorflow implementation of "Show and Tell"
A modular library built on top of Keras and TensorFlow to generate a caption in natural language for any input image.
A visual and interactive scoring environment for machine translation systems.
Evaluation Code for Text Generation Tasks
Deep RNN model(Encoder - Decoder) with Attention mechanism and Beam Search decoding for langauge translation.
Using Google Colab, we develop a NMT, language translator. Here, we do NMT to translate from English to Vietnamese.
The LSTM model generates captions for the input images after extracting features from pre-trained VGG-16 model. (Computer Vision, NLP, Deep Learning, Python)
Python code for various NLP metrics
Team project for CS 11-731 Machine Translation course.
💬 Evaluation metrics for open-domain dialog systems📏
Useful python NLP tools (evaluation, GUI interface, tokenization)
Built a classifier for evaluating quality of machine translation to predict best matching sentence to the reference sentence
Implementation of the paper "Show and Tell: A Neural Image Caption Generator" by Vinyals et al. (CVPR 2015)
10 tips for starting with a global mindset.
Image Captioning Generator Keras
PyTorch original implementation of Cross-lingual Language Model Pretraining.
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