There are 2 repositories under natual-language-processing topic.
A dataset under construction of Chinese Poetry 中文古文诗词数据集,,近1,4000诗人, 107,891唐诗,275,581宋词。
J.A.R.V.I.S is a very advanced virtual assistant who can automate almost all tasks of everything of PC & IoT. Just Say It.
"Welcome to my NLP mini-projects repository! Here, I'll share a collection of projects that explore various natural language processing (NLP) techniques and tools. From sentiment analysis to text classification, each project is designed to help you gain a better understanding of NLP and its applications. Whether you're new to NLP or an experienced
Automatic Extractive Text Summarization using TF-IDF Frequency Analysis. This is a Node.js web application using Express.js on the server side.
This project is a simple deep learning-based chatbot that uses a three-layer neural network to predict the intent of user inputs. The model architecture consists of the following layers:
Sentiment Analysis of Solar Energy Using Bidirectional Encoder Representations from Transformers
Machine and deep learning models to predict real or fake news.
The aim of this work is to solve Audio Intent Detection Problem using off the shelf libraries
CSCI-SHU 376 Natural Language Processing | Spring 2021 | Final Project
📚 DSCI 550 Project: Analysis of Cyber Phishing Emails
🐤A simple tweet classifyer with deep learning. That find diferences between two tweets using deep learning.🤖🧠
[CCS'24] Official Implementation of "Fisher Information guided Purification against Backdoor Attacks"
A tool for Raw Text processing and deciphering the Sentiment as positive or negative based on training ML (Machine Learning) models on a dataset of reviews. The Bag Of Words model is coupled with the NLP (Natural Language Processing) method for text preprocessing, tokenisation and vectorisation to predict the sentiment as positive or negative for a certain review.
A web application used to determine fake news articles utilizing Machine Learning and Natural Language Processing.
This assignment involved the implementation of a pre-trained DistilBERT model, a BERT based language model, to predict the sentiment of a given movie review.
Mini projects done for the EEE443 Neural Networks course. Includes from scratch implementations (using Numpy) of LSTM, GRU, simple RNN, a MLP structure with SGD + Momentum and more.
This is NLP model which is 98% accurate is predicting the problem related to symptoms and for mode detail have look over the notebook, uploaded on this repository.
Skip-gram is a Natural Language Processing word2vec learning algorithm that efficiently produces vector representations for a text corpus
This Python script tracks your workouts by leveraging natural language API processing to extract information about the exercises you did. It uses the Nutritionix API to obtain exercise data based on your input, and sends the workout information to a Google Sheets document using the Sheety API.
The BERT Sequence classifier combined with a Dense Neural Network is used to predict the order of sentences in a set of samples. An accuracy of 71% is achieved from the Test Set outputs.
Detailed sentiment analysis (overall and aspect based sentiment analysis) on major Singapore attractions.
Tutorials & Projects from Subject COMP90042 Natural Language Processing in the University of Melbourne
In this capstone project, we need to create a deep learning model which can explain the contents of an image in the form of speech through caption generation with an attention mechanism on Flickr8K dataset.
This project is focused on making use of the transformer as a summarizer while using the two form of attention mechanism. All the code for the transformer is implemented from scratch in order to understand the in-depth working of each component.
This is project for sequence to sequence NLP task. We developed a custom model to understand the process of task using PyTorch. We also fine tuned pre-trained transformer models to improve the performance of translation task.