Pranav Goel's repositories
Neural_Emotion_Intensity_Prediction
The code for our proposed neural models which give state-of-the-art performance for emotion intensity detection in tweets.
Sarcasm-Target-Detection
A new, manually labeled dataset for the novel task of Sarcasm Target Identification
DataStructures_Algorithms
Implementations of some useful data structures/algorithms/interesting concepts I encountered
Supervised_ML_using_scikit_learn_python
A series of python scripts to demonstrate the use of supervised machine learning algorithms implemented via the scikit-learn module of python.
api
services to access govinfo content and metadata
cl1-hw
Homework assignments for Computational Linguistics I
Data-Mining-Assignment
Data Mining Assignment
hello-world
starting something new
kd-topic-models
Repo for EMNLP 2020 paper, "Improving Neural Topic Models using Knowledge Distillation"
Machine_Learning_AndrewNG
All MATLAB scripts for the 8 assignments (100 score), as instructed in the machine learning course offered by Stanford on Coursera.
misinfo_narratives
(Currently Placeholder) Code and Data for work studying news media + misinformation
models
Models and examples built with TensorFlow
NLTK_python_sentiment_analysis
exploring nltk module pf python, and using it for sentiment analysis in various corpora, as well as live twitter analysis.
Numerical-Algorithms-Website-Implementation--
- Project Name: Implementation of Numerical Algorithms (using mathematical Libraries of Python)
PartyMatters
Data and code for "Party Matters: Enhancing Legislative Embeddings with Author Attributes for Vote Prediction"
pranav-goel.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
qanta-codalab
QANTA Competition: Baseline System
scholar.hasfailed.us
Google Scholar is a trans-exclusionary site. Don't use it. Help us demand change.
tweeteR
An R package to simplify the use of twitter API and make twitter data analysis easier
Twitter_Sarcasm_Detection
please go through the README
w-lda
Source code for paper "Topic Modeling with Wasserstein Autoencoders".