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bsc-deployment

chocolate-rating-predictions

Project 3 with Flatiron. Utilized scikit-learn's supervised learning algorithms to create a Random Forest Classifier model which predicted the rating of a chocolate bar given 5 primary features with an accuracy of 79.1 %.

company_profiles

inferential-analysis-king-county

Second project with Flatiron. Used ordinary least squared regression to analyze King County, Washington's house renovation's impact on profit as well as the renovation costs to identify individual predictor's relationships with the price.

microsoft-movie-analysis

First project with Flatiron. This project utilized descriptive statistics to observe relationships between a population of film industry data to devise recommendations for Microsoft Corporation. The project observed, specifically, the relationship between actors and film success as well as budget and its relationship to film success.

nlp-newsarticle_categorization

Fourth Project of Flatiron. Made use of natural language processing, a sub-category of machine learning, to categorize news articles based on their descriptions and headings.