mdbinger Goto Github PK
Name: Michael Binger
Type: User
Bio: Fraud Prevention Analyst. Graduate of UC Davis Data Analytics Bootcamp.
Name: Michael Binger
Type: User
Bio: Fraud Prevention Analyst. Graduate of UC Davis Data Analytics Bootcamp.
Analyzed reviews for Music products on Amazon written by members of the paid, Amazon Vine program looking for potential bias in the reviews. PySpark was used to extract and transform the review data, which was connected to an Amazon Web Service RDS and loaded into pfAdmin.
Displayed findings from analysis of bike sharing data in New York City in multiple formats via Tableau to determine viability of program operating in Des Moines, Iowa
Saving coding challenges in one location to continue to practice and demonstrate my skills
Built, trained and evaluated multiple supervised machine learning algorithms to predict credit risk for loan applicants. Algorithms ran include Random Oversampler, SMOTE, Cluster Centroids, SMOTEENN, Balanced Random Forest Classifier, and Easy Ensemble Classifier.
Preprocessed cryptocurrency dataset for Principal Component Analysis. Ran K-means algorithm to predict the optimal amount of K clusters for algorithm. Built table of currently tradable cryptocurrencies using hvplot.table function.
A simulator of the Deuces Wild Poker casino game and odds predictor
Wrote a script in Python to summarize election data and determine the results of the election.
Personal project to scrape MLB & NBA stats and analyze best performers to use for fantasy baseball and basketball drafts
Built and used github-pages to host an interactive webpage using JavaScript and HTML code to create a variety of charts displaying each patient’s belly button hygiene and bacteria that lives within their belly buttons.
Analyzed the outcomes of Kickstarter campaigns based upon the launch date, campaign goals, and other factors using Microsoft Excel charts and pivot tables
Fetched GeoJSON earthquake data from the USGS website, including coordinates and magnitudes, using JavaScript and the D3.js library. Created an interactive map from Mapbox through an API request, which has settings to toggle options to highlight major earthquakes, show tectonic plates, and change the map view
Performed a statistical analysis with t-tests and linear regression in R and R Studio on data taken from car design specs to determine if there were any differences between the cars in performance that were statistically significant.
Scraped data from several websites and used MongoDB to compile the scraped data. Created a flask application and used HTML code to display our data online in an orderly and presentable fashion.
Webpage for final project built to display player and team MLB WAR data as they relate to injuries
Extracted movie data from Kaggle and Wikipedia, transformed the data to be usable for a hackathon competition using Pandas and Jupyter Notebook, and loaded the data to SQL in PGAdmin 4 and merged the datasets.
Preprocessed dataset of over 34,000 charity organizations to compile, train, and evaluate neural network model on dataset using TensorFlow. Analyzed results of neural network model to determine if donations to organizations would help the organizations succeed.
Used SQL queries to determine the number of employees who will be eligible to retire in the next few years, broken down by company departments. Created tables to compare number of employees potentially retiring and those eligible to fill their roles.
HTML code for personal online professional portfolio and host.
Visualized and analyzed ride share data using jupyter notebook, Pandas, and Matplotlib, comparing fare and driver data in urban, suburban, and rural areas.
Determined whether student test scores are impacted by factors such as school size, school budget, student grade, etc. for a city school district using a python script in jupyter notebook with the Pandas dependency. Cleaned city school district data to eliminate problematic data that was impacting our analysis of student success on standardized tests.
Miscellaneous sports data analysis to see if I find anything interesting.
Wrote a program in VBA to filter through stock market data, analyze their performance, and created a button on the worksheet for users to run the code themselves.
Assessed the viability of opening up a joint, ice cream and surf equipment shop in Hawaii based on Hawaii’s aggregate temperature and precipitation data using Python and SQLite.
Wrote JavaScript and HTML code to create a UFO-themed, interactive webpage that displays and filters UFO sighting data by specific parameters input by webpage users.
Accessed Google Maps and Open Weather Map APIs as well as a Python script with multiple dependencies to create a responsive program that creates a travel route between user-selected cities and creates a map with markers.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.