A ML/DL based system working on SVM/BiLSTM, able to analyze Arabic Tweets and Classifies it to different types of Arabic accents.
Additional describtion about the project below.
• HTML
•CSS
•GIT
•Word2Vec
•Colab
•Python
•Gensim
•Flask
•ngrok
•keras
•TensorFlow
• Arabert pre-Trained Model https://github.com/aub-mind/arabert
git clone https://github.com/aub-mind/arabert.git
!pip install farasapy
!pip install pyarabic
from arabert.preprocess import ArabertPreprocessor
• Word2vec word embeddings from gensim library
!pip3 install --upgrade gensim
from gensim.models import word2vec
• Machine Learning Modeling
from sklearn.svm import SVC
• Deep Learning Modeling
from tensorflow.keras import Sequential
from tensorflow.keras.layers import Bidirectional
!pip install flask-ngrok
!pip install pyngrok
!curl -s https://ngrok-agent.s3.amazonaws.com/ngrok.asc | sudo tee /etc/apt/trusted.gpg.d/ngrok.asc >/dev/null && echo "deb https://ngrok-agent.s3.amazonaws.com buster main" | sudo tee /etc/apt/sources.list.d/ngrok.list && sudo apt update && sudo apt install ngrok
from flask import Flask, request, render_template
from flask_ngrok import run_with_ngrok
👤 Remon Atef Boshra
• Github @Remon128
• LinkedIn https://www.linkedin.com/in/remon-boshra/
• Twitter @remonaboshra
Give a ⭐️ if you like the project !
Contributions, issues, and feature requests are welcome!