Isana Mizuma's repositories
Lazy_LazyPredict
Utilizing LazyPredict, Feature Engine, Feature Tools: Narrow down base models automating various aspects of the eda process. Blog post at link.
depression_anxiety_stress
EDA on Kaggle dataset for predicting depression, anxiety, and stress
linear_regression_basic_explanation
Linear Regression explained in non-coding terms
covid_web_app
Web application for Streamlit. Reads data written by full repository to display plots in an interactive form. Allows for user input of vaccination rate with visualization for effect on hospitalizations and fatalities
NLP_Keras_Project
Spacy/TfidfVectorizer used to tokenize/vectorize movie descriptions. Utilized for predictions on associated movie genre. Keras used to build final model.
Phase_2_Project
Linear Regression model to predict housing prices. Features such as binning, separating houses by latitude and longitude, and census data utilized to increase prediction accuracy.
Phase_3_Project
Various machine learning models tested to make predictions on partner preference based on surveys filled prior to dating. Findings showed low accuracy utilizing pre-date data and a sharp increase when factoring partner physical attraction ratings during the date.
Time_Series_Modeling_Covid_Vax
Provides a sliding scale of COVID vaccination rates .9 to 1.9 times the actual on a per state basis. Using fbprophet, view predictions on past, present, and future COVID hospitalizations and fatalities.
flatiron_cover_letter
Repository contained Streamlit application for Flatiron Cover Letter
lesson-git-for-data-science
Lesson for using git and GitHub for data scientist. Associated lecture recording in README
recommendation_engine_basic_explanation
Recommendation Engines explained in non-coding terms
stable-diffusion-webui
Stable Diffusion web UI