hammou2020's repositories
Natural-Language-Processing
Implementation of multiple NLP approaches, in order to identify fake product reviews at one of the leader Virtual Merchants of the world.
project006
Natural language processing and web scraping
COVID19-Urban-Sentiment-Analysis
Arabic and English data analysis on the first weeks of COVID-19 quarantine with sentiment analysis and analyzing social media activity with respect to urban features of the governorates in Egypt.
MiAI_NLP_02
Demo of using Word2Vec, FastText to classify document
Twitter_Sentiment_Analysis
This repository details the various approach and algorithms used for modelling Sentiment Analyser.
CovidBot-Telegram
a conversational agent in Arabic Darija called CovidBot which aims to inform Moroccans about the evolution of the CoronaVirus pandemic in the kingdom, and also to help them better understand this virus, how to protect themselves from it and how to fight it.
Text_Classification_Tweets
Sentiment Analysis and Text Classification NLP task with Fasttext and Neural Network
FAKE-NEWS-DETECTION
A MACHINE LEARNING project that predicts whether a news is real or fake.
Machine-Learning-Project
Fake Review dectection using Yelp Restaurant Data
nlp-in-python-tutorial
comparing stand up comedians using natural language processing
Jupyter-Sentiment-Analysis-Video-games-reviews
Reviews of video-games.
Sentiment-VADER-NLTK
Sentiment analysis on COVID19 tweets.
Hotel-Review
Sentiment Analysis of Hotel Reviews using Natural Language Processing and Machine Learning
Airline-Twitter-Sentiment-Analysis
This multi-class sentiment analysis was carried out using three classification algorithms: Multinomial Naïve Bayes, Support Vector Matrix(SVM), and Random Forest. I also used logistic regression and VADER algorithms.
Twitter-Sentiment-and-Customer-Churn-Detection
Performed customer sentiment analysis on the tweets related to 4 major streaming services, applied various NLP and text analysis tools, and created multiple ensemble and deep learning classification models to implement churn detection and performed a rule-based feature extraction to find out the reasons for churn. Created a visualization dashboard using Plotly and Dash and deployed on Heroku.
fake-review-detection-1
fake review detection
spam-classifier
A simple program using Naive Bayes Algorithm for classification of spam mails
Sentimental-Analysis
Sentimental Analysis of students reviews about teachers, how they deal with in class room with students.
NLP-spam-filter
This model will detect if a message is spam or good "ham"
COVID-19-Arabic-Tweets-Dataset
The repository contains a collection of Arabic tweets IDs associated with the novel coronavirus COVID-19. The dataset contains Tweets' ids from 2020-01-01 to 2020-04-15. The Twitter search API was used to gather real-time tweets that contained specific keywords in the Arabic language. The dataset contains almost eight millions and half Arabic tweets.
NLP-Spam-Ham-Classifier
A Machine learning classifier to predict whether the SMS is Spam or Ham by using Natural Language Processing(NLP)
Amazon-Review-Data-Analysis
Sentiment Analysis and Recommender System based on Amazon Reviews
Twitter_Sentiment_Analysis-Using-ML-and-NLP
The objective of this project is to detect hate speech in tweets. For the sake of simplicity, we say a tweet contains hate speech if it has a racist or sexist sentiment associated with it. So, the task is to classify racist or sexist tweets from other tweets.