Project 1: Data Science Salary Estimator: Project Overview Created a tool that estimates data science salaries (MAE ~ $ 9K) to help data scientists negotiate their income when they get a job. Scraped over 1000 job descriptions from glassdoor using python and selenium Engineered features from the text of each job description to quantify the value companies put on python, excel, aws, and spark. Optimized Linear, Lasso, and Random Forest Regressors using GridsearchCV to reach the best model.

Project 2: Movie Recommendation Engine Imported a movie dataset csv file and used sklearn and machine learning algorithms to recommend movies based off your inputed favorite. Engineered features to use in the algorithm: “overview”, “keywords”, “cast”, “genres”, “director”. Combined the features into one string and used CountVectorize to convert the collection of text to token counts Used the Cosine Similarity to create a matrix showing the similar movies based off the features combined Created a function to be able to look through then index of movies to return a movie title that matches the similarity index.