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Mohamed Wael Mohamed Zaki's Projects

bigmartsales icon bigmartsales

The data scientists at BigMart have collected 2013 sales data for 1559 products across 10 stores in different cities. Also, certain attributes of each product and store have been defined. The aim is to build a predictive model and find out the sales of each product at a particular store.

data-visualization-using-r icon data-visualization-using-r

Using the dataset “diabetes.CSV” dataset which is a metabolic disease in which the body’s inability to produce insulin causes elevated levels of glucose in the blood.

designpatterns icon designpatterns

This repository contains most famous design patterns implemented in java - DP Course

gp_product_recommendation_system icon gp_product_recommendation_system

The recommendation system uses ResNet50 for feature extraction, enhancing visual understanding and enabling accurate product recommendations.

risk-and-returns-the-sharpe-ratio icon risk-and-returns-the-sharpe-ratio

When you assess whether to invest in an asset, you want to look not only at how much money you could make but also at how much risk you are taking. The Sharpe Ratio, developed by Nobel Prize winner William Sharpe some 50 years ago, does precisely this: it compares the return of an investment to that of an alternative and relates the relative return to the risk of the investment, measured by the standard deviation of returns.

robotproject1 icon robotproject1

Dell Technologies' Summer Academy - Automation Testing Session

titanic-data-science-solution icon titanic-data-science-solution

Titanic Data Science Solution is a Python-based solution using pandas, numpy, and data visualization libraries like seaborn and matplotlib. It analyzes and visualizes Titanic passenger data to predict survival rates, helping to understand the factors that influenced survival on the ill-fated voyage.

tmdb-movie-dataset-using-ai-ml icon tmdb-movie-dataset-using-ai-ml

The idea behind this ML project is to build a model that will classify how much loan the user can take. It is based on the user’s marital status, education, number of dependents, and employment. You can build a linear model for this project.

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