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Sam Shamsan's Projects

allennlp icon allennlp

An open-source NLP research library, built on PyTorch.

aoc_id icon aoc_id

Arabic Dialect Identification on AOC data.

clipper_game_sentiment_analysis icon clipper_game_sentiment_analysis

This is s Sentiment Analysis for the data collect after the game of clipper, containing tweets downloaded from Twitter. These tweets were created on Sunday night, right after the Clippers game.

cosine icon cosine

This is the code for our paper `Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach' (to appear at NAACL-HLT 2021).

courses icon courses

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

doc2vec icon doc2vec

Python scripts for training/testing paragraph vectors

emoji icon emoji

emoji terminal output for Python

ernie icon ernie

An Implementation of ERNIE For Language Understanding (including Pre-training models and Fine-tuning tools)

ewise icon ewise

ACL 2019: Zero-shot Word Sense Disambiguation using Sense Definition Embedding

fastchat icon fastchat

An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and FastChat-T5.

flowise icon flowise

Drag & drop UI to build your customized LLM flow

getting-things-done-with-pytorch icon getting-things-done-with-pytorch

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.

gsrl icon gsrl

GSRL is a seq2seq model for end-to-end dependency- and span-based SRL (IJCAI2021).

mindmeld icon mindmeld

An Open Source Conversational AI Platform for Deep-Domain Voice Interfaces and Chatbots.

ml-dl-rl_codes icon ml-dl-rl_codes

This repository contains codes starting from the basic machine learning to advanced topics in Ipython Notebooks.

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