Wessam Walid (wessamsw)

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Wessam Walid's repositories

WorldQuant-Data-Science-Program

Here you can find all the 8 projects of WorldQuant's Data Science Program along with my certification. I had no references to get clues from when studying this program so I hope this proves handy to others.

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Airline-Reservation-System

This is a program regarding Airline Reservation System made by C++ with a GUI of C# extension tailored for C++.

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Airline_Passenger_Satisfaction

A classification model used to classify the passengers satisfaction from 1-5 in an airline system. Dataset is analysed, pre-processed and necessary visualisations are made. Two models are made. One using Logistic Regression and the other using KNN. Both of the models are evaluated.

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Applai-CV23

Applai Computer Vision Summer Training 2023. It is a one-month training with an assignment each week wrapping up with a big project by the end of the training

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Blackjack

A blackjack game coded with Java. The bets are not included in the code with a simple interface

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Brain-Tumor-Detection

A project using brain MRI pictures to build models help classify whether a brain MRI indicates whether the patient has a tumour or not

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California_Houses_Price_Prediction

A regression model used to predict the price of a house in California based on the data inputted. Model is implemented using three methods: VIF, Linear, Lasso & Ridge regression. Dataset is analysed and processed beforehand.

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Car-Price-Prediction

Machine learning project using python libraries and data analysis that creates a model that predicts the car price. Model is then used in a webapp implemented flask to provide a GUI.

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Churn-Modelling-10-Models-

10 classification models used to target a binary variable reflecting the fact whether the customer left the bank (closed his account) or he continues to be a customer.

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Credit-Card-Fraud-Detection

Using a dataset provided by Kaggle, It is important that credit card companies are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase. I will use various predictive models to see how accurate they are in detecting whether a transaction is a normal payment or a fraud.

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Data-Science-Job-Salaries

With the emerging field of data science, it is important for us to figure out how can we predict a data scientist's salary and what are they key attributes that play a big role in deciding an individual's salary. Using the dataset provided by Kaggle, data is analysed, preprocessed and tested with several models for better accuracy. Model is then saved and deployed using heroku and flask.

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Events-Schedular

An events scheduler programmed with C++ with a GUI of C# extension tailored for C++.

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Heart-Disease-Prediction

Analysing a health disease dataset from Kaggle and using several models to predict what are the personal key indicators of heart disease. Also model is deployed to help nutritionists keep track of their patients data or health application to warn the users.

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Image_Classification_CNN

A natural scene imagery classification CNN made with InceptionV3 model and ResNet with accuracies 92% and 90% respectively. Data is split 70% for training and 30% for testing. I participated in Sprints Academy AI program competition with this project.

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Indian-Flight-Price-Prediction

Analysing flights information dataset from Kaggle and using several models to predict the flight ticket. Also model is deployed to help users or new airports to predict the expected flight ticket price.

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Intrusion-Detection

Using a dataset provided by Kaggle, it is vital to make sure people are safe in their houses and so I created an intrusion detection model using SVM (4 different types).

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Merge-Sort

The infamous Merge Sort algorithm implemented using OS concepts such as threading, multithreading and semaphores in C#

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RSNA-Fracture-Detection

Over 1.5 million spine fractures occur annually in the United States alone resulting in over 17,730 spinal cord injuries annually. The most common site of spine fracture is the cervical spine. There has been a rise in the incidence of spinal fractures in the elderly and in this population, fractures can be more difficult to detect on imaging due to superimposed degenerative disease and osteoporosis. Imaging diagnosis of adult spine fractures is now almost exclusively performed with computed tomography (CT) instead of radiographs (x-rays). Quickly detecting and determining the location of any vertebral fractures is essential to prevent neurologic deterioration and paralysis after trauma.

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Stellar-Classification-SDSS17

A stellar dataset from Kaggle analysed, pre-processed and four models (SVM, Random Forest, KNN & Logistic Regression) are made with accuracies over 95%.

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