Mohammad Dabbous's repositories
Amazon_Vine_Analysis
Analyze a data set from the Amazon Vine program to determine if there is any bias toward favorable reviews from Vine members in your dataset.
Credit_Risk_Analysis
Assess credit risk of applicants using supervised machine learning. Several different machine learning techniques such as SMOTE, SMOTEENN, RANDOM FOREST, EASY ENSEMBLE were applied, the models were assessed using accuracy score, precision and accuracy to choose the best technique that applies to this type of problem.
Cryptocurrencies
A prominent investment bank, is interested in offering a new cryptocurrency investment portfolio for its customers, but due to the large number exisiting cryptocurrencies, some work must be done to create a report that includes what cryptocurrencies are on the trading market and how they could be grouped to create a classification system for this new investment.
Machine-Learning-Investment
Scraping data sets from Yahoo Finance API using Python and Pandas, applying machine learning techniques to predict and visualize stock prices.
School_District_Analysis
The purpose of this analysis is to use and analyze data on student funding and student's standardized test scores. This data will be used to analyze school performance which will assist the school board in making key decisions regarding schoools budgets and priorities.
bikesharing
This analysis is done in Tableau to understand, analyze and draw conclusions from a bike sharing service in the city of New York in order to apply these observations to the bike sharing service intended to be established in the city of Des Moines.
Improbable-Beef
This project aims at analyzing data from many volunteers to identify the top 10 bacterial species in their belly buttons. These bacteria will help Improbable-Beef in manufacturing synthetic beef.
Kickstarter-analysis
Performing analysis on kickstarter data to uncover trends
Pewlett-Hackard-Analysis.
Utilizing Postgres SQL to help Pewlett Hackard to realize how many employees will be retiring this year and categorizing them by their title, as well as count the number of employees who qualify to be in the mentorship program to train new employees.
Mapping_Earthquakes.
This project uses leaflet to map earthquakes, major earthquakes and the tectonic plat in the earth. It is a combination of java script (leaflet), HTML to showcase the map and CSS for formatting.
PyBer_Analysis
PyBer company is conducting an analysis on data collected to examine the relation between different city type(urban, rural and suburban) and the number of drivers and riders, as well as the percentage of total fares riders and drivers by type of city. Analysis is to be concducted and visualizations are to be produced.
surfs_up.
The purpose of this analysis is to obtain more information about temperature trends before opening the surf shop. Analyzing temperature data for the months of June and December in Oahu, in order to determine if the surf and ice cream shop business is sustainable year-round.