Pinned Repositories
aehabV
AirlineDW
Data Vault model for analyzing the flight activity and reservation processes of a major airline company. Provides SQL scripts, queries, and reports for gaining insights into business operations and improving performance.
Arabic-Book-Recommendation-and-Question-Answering-System
The dataset was first scraped from an Arabic book library website, then cleansed of non-Arabic words, numerals, and tags before going through multiple preprocessing steps. Second, after applying the TF-IDF vectorizer, we used the Random Forest Classifier (RFC) algorithm to be trained on the data. Finally, two Question-Answer datasets were created manually. The input query was matched with the questions within the two datasets to retrieve the most relevant answer.
BashSQL
The MySQL Bash project is a simulation of a MySQL database that allows users to create and delete database users, create and delete databases, create tables, insert rows, and select data from tables. It's contained in a directory called MySQL, and the main script is main.sh.
Building-Gradient-Descent-Methods-from-Scratch
Implemented optimization algorithms, including Momentum, AdaGrad, RMSProp, and Adam, from scratch using only NumPy in Python. Implemented the Broyden-Fletcher-Goldfarb-Shanno (BFGS) optimizer and conducted a comparative analysis of its results with those obtained using Adam.
Evolving-CNNs-using-GA
Evolving Architectures for Convolutional Neural Networks using the Genetic Algorithm
Face-Generation-using-GANs
The CelebA dataset was used to train a DCGAN (Deep Convolutional Generative Adversarial Network). The project was broken down into a series of tasks, from loading in data to defining and training adversarial networks. The trained network generated new images of faces that seemed to be fairly realistic with reduced noise
Hate-Speech-Detection-on-Arabic-Tweets
We utilized a pre-trained model to classify Arabic text. After conducting extensive research, we found that MarBERT was the best model for classifying Arabic offensive tweets. It focuses on dialectal Arabic (DA) and Modern Standard Arabic (MSA). The competition involves two shared sub-tasks: detecting whether a tweet is offensive or not; and detecting whether a tweet contains hate speech or not. It detected offensive sentences with 84.9% accuracy and F1-Score of 83.5%, and hate speech with 93.4% accuracy and F1-Score of 80.4%.
Indeed-fake-job-posting-prediction
A machine learning model is built using PySpark's MLlib library to automatically flag suspicious job postings on Indeed.com. The dataset includes 18,000 job descriptions, out of which about 800 are fake.
Paint-Brush-Applet
Paint Brush is an Applet-based drawing app that uses OOP design. It enables users to draw basic shapes with different colors and line strokes, and includes a Clear All button. The app also supports saving and loading drawings as images, making it a useful tool for sharing and archiving artwork.
aehabV's Repositories
aehabV/Hate-Speech-Detection-on-Arabic-Tweets
We utilized a pre-trained model to classify Arabic text. After conducting extensive research, we found that MarBERT was the best model for classifying Arabic offensive tweets. It focuses on dialectal Arabic (DA) and Modern Standard Arabic (MSA). The competition involves two shared sub-tasks: detecting whether a tweet is offensive or not; and detecting whether a tweet contains hate speech or not. It detected offensive sentences with 84.9% accuracy and F1-Score of 83.5%, and hate speech with 93.4% accuracy and F1-Score of 80.4%.
aehabV/AirlineDW
Data Vault model for analyzing the flight activity and reservation processes of a major airline company. Provides SQL scripts, queries, and reports for gaining insights into business operations and improving performance.
aehabV/Arabic-Book-Recommendation-and-Question-Answering-System
The dataset was first scraped from an Arabic book library website, then cleansed of non-Arabic words, numerals, and tags before going through multiple preprocessing steps. Second, after applying the TF-IDF vectorizer, we used the Random Forest Classifier (RFC) algorithm to be trained on the data. Finally, two Question-Answer datasets were created manually. The input query was matched with the questions within the two datasets to retrieve the most relevant answer.
aehabV/Building-Gradient-Descent-Methods-from-Scratch
Implemented optimization algorithms, including Momentum, AdaGrad, RMSProp, and Adam, from scratch using only NumPy in Python. Implemented the Broyden-Fletcher-Goldfarb-Shanno (BFGS) optimizer and conducted a comparative analysis of its results with those obtained using Adam.
aehabV/Indeed-fake-job-posting-prediction
A machine learning model is built using PySpark's MLlib library to automatically flag suspicious job postings on Indeed.com. The dataset includes 18,000 job descriptions, out of which about 800 are fake.
aehabV/Paint-Brush-Applet
Paint Brush is an Applet-based drawing app that uses OOP design. It enables users to draw basic shapes with different colors and line strokes, and includes a Clear All button. The app also supports saving and loading drawings as images, making it a useful tool for sharing and archiving artwork.
aehabV/aehabV
aehabV/BashSQL
The MySQL Bash project is a simulation of a MySQL database that allows users to create and delete database users, create and delete databases, create tables, insert rows, and select data from tables. It's contained in a directory called MySQL, and the main script is main.sh.
aehabV/Cement-Strength-Prediction-with-PySpark
A machine learning model that predicts the strength of cement based on its ingredients using PySpark's MLlib library.
aehabV/Compiler-Project-Lexical-Analyzer-
aehabV/Evolving-CNNs-using-GA
Evolving Architectures for Convolutional Neural Networks using the Genetic Algorithm
aehabV/Face-Generation-using-GANs
The CelebA dataset was used to train a DCGAN (Deep Convolutional Generative Adversarial Network). The project was broken down into a series of tasks, from loading in data to defining and training adversarial networks. The trained network generated new images of faces that seemed to be fairly realistic with reduced noise
aehabV/Query-a-Digital-Music-Store-Database
The goal is to address a series of questions to help the Chinook team members understand the media in their store, their customers and employees, and their invoicing information.
aehabV/Selection-sort-for-characters-and-numbers-with-MIPS
The project is an implementation of the selection sort algorithm in MIPS assembly language to sort both characters and integers. The program loads the input array into the .data section of the MIPS program and calls the selection_sort function to sort the array in place.
aehabV/Customer-Behavior-Analysis-and-Segmentation
This project utilizes SQL analytical functions to analyze customer behavior and segment customers into different groups based on their purchasing patterns. It involves exploring the OnlineRetail dataset and answering key business questions related to customer behavior.