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Abdul El Barkouki's Projects

amazon_vine_analysis icon amazon_vine_analysis

Given access to approximately 50 datasets, each containing reviews of a specific product and written by members of the paid Amazon Vine Program. We used PySpark to perform the ETL process to extract the dataset, transform the data, connect to an AWS RDS instance, and load the transformed data into PgAdmin.

belly-button-biodiversity icon belly-button-biodiversity

Belly Button Biodiversity Study: A project visualizing bacteria data from volunteers' belly buttons with Plotly.

bikesharing icon bikesharing

We worked with data visualization software "Tableau" to present a business proposal for a bike-sharing company in Des Moines, Iowa. The study was based on an actual NYC bike-sharing company.

credit_risk_analysis icon credit_risk_analysis

Analyze of several Machine Learning techniques in order to help Jill decide on a most effective Machine Learning Model to analyze Credit Card Risk applications.

cryptocurrencies icon cryptocurrencies

Using Unsupervised Machine Learning, we created an analysis for a client who is preparing to get into the cryptocurrency market.

election_analysis icon election_analysis

Using Python - We helped with an Election Audit of the results for a U.S Congressional Election in the state of Colorado.

kickstarter-analysis icon kickstarter-analysis

In this project we are helping Louise understand other campaigns’ outcomes based on their launch dates and their funding goals. We want to provide Louis with some key factors to make her fundraising campaign successful.

linear_regression_salary icon linear_regression_salary

There are a number of classification algorithms that can be used to determine loan elgibility. Some algorithms run better than others. We built a loan approver using different Supervised Machine Learning algorithms and compared their accuracies and performances

mapping_earthquakes icon mapping_earthquakes

Using Leaflet.js Application Programming Interface (API), we populated an interactive Geographical map with GeoJSON earthquake data, collected from the U.S. Geological Survey website, over the previous seven days.

mechacar_statistical_analysis icon mechacar_statistical_analysis

Using R, we designed a statistical study to compare performance of the MechaCar vehicles against performance of vehicles from other manufacturers.

mission-to-mars icon mission-to-mars

Web data extraction is used for extracting data from external websites. In this assignment, 5 different websites are scraped and the results are stored in MongoDB. Flask application is then used to render the scraped data to a HTML webpage.

movies-etl icon movies-etl

Extracting, Transforming and Loading movie data, from Wikipedia, Kaggle, and local csv/Json files. Data was then transformed to an easy to read and access database on SQL for further queries.

pewlett-hackard-analysis icon pewlett-hackard-analysis

Using SQL database and analysis, we helped Pewlett-Hackard analyze and prepare for an upcoming "Silver Tsunami" event. This "Tsunami" will have several long term employees retire and will require the company to prepare for their departure, then properly plan their replacement.

pyber_analysis icon pyber_analysis

The purpose of this analysis was to help PyBer, a Python based ride-sharing app company, better understand their accessibility and affordability rates in different city types, such as Urban, Suburban, or Rural.

school_district_analysis icon school_district_analysis

An anlaysis of student funding and standardized testing results across a school district to identify any performance trends and patterns within the district.

surfs_up icon surfs_up

Advanced Data Storage and Data Retrieval with `Jupyter Notebook`, `SQLite` and `SQLAlchemy`

ufos icon ufos

A webpage designed to display an article on UFO’s along with filterable options to select UFO sightings in different regions, based on different filters, such as date of sighting, state, shape of UFO, etc..

world_weather_analysis icon world_weather_analysis

Using APIs to collect and analyze weather and map data, we were able to provide customers and travelers with enough insights and information to plan their trips, based on their weather preferences, on their search page on the app.

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