Durga Prasad Manukonda's Projects
Let's learn a new technology every week. A new technology blog every Sunday in 2016.
Materials from the ACL 2018 tutorial on neural semantic parsing
ADAM - A Question Answering System. Inspired from IBM Watson
AFINN sentiment analysis in Python
A powerful and intuitive WYSIWYG interface that allows anyone to create Machine Learning models!
An open-source NLP research library, built on PyTorch.
Allosaurus is a pretrained universal phone recognizer for more than 2000 languages
Relevant Entity Selection for KG Bootstrapping via Analogical Pruning
The aim of the project is the intend to do statistical analysis project using Big Data Analytical tools is to analysis World Development Indicator data which give the countries current development status in the international level. Identify effective public and private actions, set goals and targets, monitor progress and evaluate impacts. They are also an essential tool of good government, providing a means for people to assess what governments do and helping them to participate directly in the development process. Environment: Rhadoop, Python and ipython shell(numpy, pandas, SciPy, matplotlib), R. R-Packages Need: WDI, ggplot2 Techniques Used: Simple Linear regression and correlation, Spearman’s Pair wise or Rank Order correlation, Time series analysis.
A collections of public and free annotated datasets of relationships between entities/nominals (Portuguese and English)
Telugu, Tamil, Hindi, KannaDa, Malayalam NER tagger with POS tagging. Secured 1st rank(Team Name: rohithkodali). Check accuracy of each language in PNG.
Aspect level sentiment classification is a fundamental task in the field of sentiment analysis. People write reviews for products and services. Both products and services have different aspects on which people give their opinions. Here people talked about two aspects of restaurant domain, food and staff. Given a sentence and an aspect occurring in the sentence, this task aims given a set of sentences, classify each word in each sentence into Aspect (ASP-Positive) and Non - Aspect(NASP-Negative) and second is to cluster the list of aspects into ‘n’ clusters.
End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow
Repository with all what is necessary for sentiment analysis and related areas
The code for the ACL 2017 paper "Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling"
TensorFlow code and pre-trained models for BERT
This repo contains a PyTorch implementation of a pretrained BERT model for multi-label text classification.
Basic Model for Sentiment Analysis - Reading English Flat File, parsing the files correctly in different segments/sentences Text Cleaning (Stop Words, Links, Special Characters,etc) Creating bags of words - (manually or module/library) Training and testing Classifier (mostly Naive Bayes Classifier)
A powerful Rasa UI to build advanced AI assistants.
We performed climate change stance classification on a pre-labelled Twitter dataset and applied it to access trends between 2014 and 2021.
Clinical Named Entity Recognition system (CliNER) is an open-source natural language processing system for named entity recognition in clinical text of electronic health records.
Code For Medium Article: "How To Create Natural Language Semantic Search for Arbitrary Objects With Deep Learning"
Cheat Sheets
The Natural Language Decathlon: A Multitask Challenge for NLP