Name: Mohamed Wael Mohamed Zaki
Type: User
Bio: Pursing to be a successful data scientist.
I am always on the lookout for hard, high-impact projects.
Location: Ismailia, Egypt
Mohamed Wael Mohamed Zaki's Projects
A list of AI/ML driven companies in Egypt
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.
Resoruce to help you to prepare for your comming data science interviews
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.
Statistical Analysis for a certain dataset. ("bestsellers with categories.csv")
This repository contains most famous design patterns implemented in java - DP Course
Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.
The recommendation system uses ResNet50 for feature extraction, enhancing visual understanding and enabling accurate product recommendations.
:computer: Learn to make machines learn so that you don't have to struggle to program them; The ultimate list
The Data set describe the categories of phones. Start by analyzing the data and then cluster it in a new column then use a supervised model to predict the new column.
Config files for my GitHub profile.
Movie Recommendation System With Python And Pandas: Data Project
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.
Dell Technologies' Summer Academy - Automation Testing Session
Source code for Twitter's Recommendation Algorithm
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.
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.