Housing Prices Prediction in Buenos Aires, Argentina

In this project, learned about data wrangling and visualization skills and move from descriptive to predictive data science. The focus is real estate, and created a machine learning model that predicts apartment prices in Buenos Aires, Argentina. Created a linear regression model using the scikit-learn library. Built a data pipeline for imputing missing values and encoding categorical features. Improved model performance by reducing overfitting. Created a dynamic dashboard for interacting with completed model.

Predicting Air Quality in Dar es Salaam, Africa

Data was collected from querying a MongoDB database of one of Africa’s largest open data platforms openAfrica and built a timeseries model to predict PM 2.5 readings. Created a wrangle function that will extract the PM2.5 readings from the site that has the most total readings in the Dar es Salaam collection, localize reading time stamps to the timezone for “Africa/Dar_es_Salaam”, remove all outlier PM2.5 readings that are above 100.

Predicting Air Quality in Nairobi

In this project, I have worked with data from one of Africa’s largest open data platforms openAfrica, looked at air quality data from Nairobi and built a timeseries model to predict PM 2.5 readings throughout the day. Get data by querying a MongoDB database. Prepared time series data for analysis. Created ACF, PACF plot for the data. Built autoregression model, ARMA model. Improved a model by tuning its hyperparameters. Link to GitHub Repository