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Michael Mishkanian's Projects

amazon_vine_analysis icon amazon_vine_analysis

Analysis of a customer review dataset from Amazon. ETL process is performed using PySpark and is connected to an AWS RDS instance. Pandas is used to determine if there is any bias towards favorable reviews from "Amazon Vine" members.

bikesharing icon bikesharing

Visual business proposal created using Tableau. Data is modified using Pandas to properly generate graphs.

credit_risk_analysis icon credit_risk_analysis

Six different techniques are employed to train and evaluate models with unbalanced classes. Algorithms are used to predict credit risk. Performance of these different models is compared and recommendations are suggested based on results.

cryptocurrencies icon cryptocurrencies

Cryptocurrency data is preprocessed using Pandas to fit Unsupervised Machine Learning models. A clustering algorithm is used to group data. hvPlot visualization are used to share results.

election_analysis icon election_analysis

Audit and analysis of an election to determine winner. Python script created to analyze CSV file.

mapping_earthquakes icon mapping_earthquakes

Creating visualizations of earthquake data from the U.S. Geological Survey using Leaflet.js and Mapbox API. Multiple map styles and popup markers are also included.

math_tutor_cpp icon math_tutor_cpp

C++ program that can be used as a math tutor for young students to practice adding numbers.

mechacar_statistical_analysis icon mechacar_statistical_analysis

Statistical analysis of a product prototype using R and tidyverse. Multiple linear regressions, statistical summaries, and t-tests are used for analysis and predictions. A study is also designed to compare this product to the competition.

mission-to-mars icon mission-to-mars

A web app is built to scrape several NASA websites for the most recent Mars data. The extracted data is stored in a NoSQL database and then an HTML page is created to display the findings.

movies-etl icon movies-etl

Creation of an automated pipeline that extracts and transforms movie data from Wikipedia, Kaggle, and MovieLens. The cleaned data is loaded into a PostgreSQL database.

neural_network_charity_analysis icon neural_network_charity_analysis

Created a deep-learning neural network to analyze and classify the success of charitable donations. Trained models are stored for future use. Attempts are made to optimize the working model.

pewlett-hackard-analysis icon pewlett-hackard-analysis

Investigation of a company's employment records using PostgreSQL to find the number of retiring employees by position. Potential solutions are also discussed.

plotly_deploy.io icon plotly_deploy.io

Built an interactive dashboard using event handlers in JavaScript and Plotly.js to create graphs. The finished product is deployed to GitHub Pages.

pong_game icon pong_game

Created the classic game Pong using Python.

pyber_analysis icon pyber_analysis

Ride-sharing data is analyzed to provide a visual summary of performance and offer data driven suggestions.

school_district_analysis icon school_district_analysis

Analysis of school district data, such as school budgets and student performance, to uncover trends and draw conclusions.

surfs_up icon surfs_up

Analyzing temperature trends and generating statistical summaries. Used SQLAlchemy to connect to and query a SQLite database.

ufos icon ufos

Creation of a UFO webpage, which has a dynamic table that allow users to filter for multiple criteria at the same time. This webpage is built with JavaScript, HTML, and CSS.

world-weather-analysis icon world-weather-analysis

Retrieval and analysis of weather data using OpenWeatherMap API. Data is used to created a vacation and travel itinerary using Google Maps Platform APIs.

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