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https://github.com/mrandolph95/grad-projects

Projects completed during my ASU grad program for Social Data Science.
https://github.com/mrandolph95/grad-projects

beautifulsoup nltk numpy pandas regression-analysis sckiit-learn seaborn selenium

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Projects completed during my ASU grad program for Social Data Science.

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# MLR_Portfolio
Data Science Portfolio

# [Project 1: Naive Bayes Classifier Using NLP](https://github.com/mrandolph95/STC510/blob/main/modulefive%20(2).ipynb)
* Converted large JSON file of "Jeopardy!" records to data frame with 216,930 rows.
* Sparsed "Jeopardy!" questions and transformed them into vectors to predict their difficulty.
* Packages: scikit-learn, NLTK, and pandas

# [Project 2: Descriptive Statistics Using GoFundMe Data](https://github.com/mrandolph95/STC551/blob/main/STC551_Module_1%2C_desc_stats.ipynb)
* Aggregated and prepared 1,242 rows of data to find variables, summarize information, and highlight possible relationships using Python.
* Created box plots, histograms, and scatterplots to help visualize data.
* Packages: pandas, plotly, and NumPy

# [Project 3: Regression Analysis Using Phoenix Crime Data](https://github.com/mrandolph95/STC510/blob/main/Mod3.ipynb)
* Utilized Python to clean 6,963 rows of crime data for analysis and grouped variables.
* Generated scatterplots and bar graphs to visually supplement data.
* Packages: seaborn, pandas, matplotlib, NumPy

# [Project 4: Web Scraping with Craigslist](https://github.com/mrandolph95/STC510/blob/main/mod4.ipynb)
* Built a customized python-based web scraper to search keywords within Craigslist ads on a daily basis.
* Packages: selenium, BeautifulSoup, webdriver, pandas