Do you want to learn more about the modern deep learning techniques applied in NLP, and keep track of emerging trends, dataset/code releases, and state of the results in the field? In collaboration with Soujanya Poria (an NLP researcher), we are open sourcing an online learning resource for NLP researchers and developers called “NLP Overview”.
The project contains an overview of recent trends in deep learning based natural language processing (NLP). It summarizes implementation details behind deep learning techniques such as recurrent neural networks (RNNs), convolutional neural networks (CNNs), and reinforcement learning used for various NLP tasks and applications. The site also contains a summary of state of the art results for NLP tasks such as machine translation, question answering, and dialogue systems. You can find the learning resource at the following address: https://nlpoverview.com. A snapshot of the website is provided below:
The main motivations for this project are as follows:
-
Maintain an up-to-date learning resource that integrates important information related to NLP research, such as state of the art results, theoretical details, emerging concepts and applications, new benchmark datasets, code/dataset releases, etc.
-
Create a friendly and open resource to help guide researchers and anyone interested to learn about modern techniques applied to NLP
-
A collaborative project where expert researchers can suggest changes (e.g., incorporate SOTA results) based on their recent findings and experimental results
This book is published as open source and compliments well with other popular NLP resources such as Sebastian Ruder’s NLP Progress website. We are calling for contributions from the NLP and machine learning community to help us improve and keep the site up-to-date. We have created a GitHub repository for the website where pull requests can be made.