Stephen Barrie's repositories
stock-markets-analytics-zoomcamp
Course Materials for Analytics in Stock Markets Zoomcamp
disaster_response_NLP_pipeline
ETL : Python script, csv, clean with pandas, save to SQLITE database. NLP ML pipeline: tokenizes raw text and classifies. Visualization in Flask app
Agri_Dashboard
Dashboard creating using data from World Bank API,. Front-end Plotly, Bootstrap. Back-end Flask. Deployment Heroku
stack_overflow_developer_survey_2023
Detailed analysis of the Stack Overflow Developer Survey 2023. Link to the blog post below :
stackoverflow
Findings from Stackoverflow 2017
Bayesian-inference
A/B testing, decision analysis, and linear regression modeling using a Bayesian approach
pymc
Bayesian Modeling and Probabilistic Programming in Python
Stephen137.github.io
Data blog page
statistical_inference
Moving from descriptive statistics to inferential statistics, leveraging parametric and non-parametric using SciPy to measure strength, and bootstrapping to address imbalanced datasets
pymc-marketing
Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.
fraud_detection
Rebalance dataset using sampling techniques (SMOTE), leveraging ensemble, K-means, and text mining LDA (Latent Dirichlet Allocation) models to detect fraud
customer_lifetime_value
Transformation of complex Google Merchandise Store BigQuery raw dataset, into business insights and actionable marketing outcomes using SQL and pandas. Baseline XGBoost regression and classification models to predict customer spend. Explore Dash app from link below.
end_to_end_data_pipeline
Fully automated csv to dashboard pipeline using Terraform, Google Cloud Storage, BigQuery, dbt, Prefect and Looker Studio. Peer ranked 9 of 298. Explore the dashboard below
Machine-Learning-Engineer-Learning-Path
A curated collection of on-demand courses, labs, and skill badges that provide real-world, hands-on experience using Google Cloud technologies essential to the ML Engineer role.
Advent_of_Code_2023
Advent of Code is an Advent calendar of programming puzzles created by Eric Wastl
Hypotheses_Testing
Statistical analysis of a sample of patients who were evaluated for heart disease at the Cleveland Clinic Foundation. The data was downloaded from the UCI Machine Learning Repository below, and then cleaned for analysis.
urban_accessibility
Geolocation project to estimate amenity accessibility. Combines amenity data harvested from OSM, population data sourced from WorldPop Hub and leverages Uber's H3 grid system to provide location intelligence.
Imagery-in-Action
Learn how to use ArcGIS Pro, ArcGIS Online, and other apps to visualize, analyze, and derive information from imagery and remote sensing.
Edinburgh_Airbnb
Perform a spatial join and create an interactive Felt choropleth map of Airbnb density per km2 at data zone granular level.
ESRI-Spatial-Data-Science
Exploring the application of spatial data science to uncover hidden patterns and improve predictive modeling, using powerful analytical tools in Esri's ArcGIS software and learning how to integrate popular open data science packages into my analyses.
Scottish-Index-of-Multiple-Deprivation
The aim of this project is to analyse and visualise the Scottish Index of Multiple Deprivation (SIMD) using a combination of pandas, geopandas, seaborn, matplotlib, QGIS and ArcGis Pro. The insights derived could be used by Scottish Government to help shape future resource allocation strategy.
Automating-GIS-processes
Geographic data analysis using Python from the course developed at the Department of Geosciences and Geography, University of Helsinki, Finland.
ARSET
Collection of training programs created by NASA's Applied Remote Sensing Training Program (ARSET)
Satellite-Data-for-Air-Quality-Environmental-Justice-and-Equity-Applications
Demonstrate how remotely-sensed environmental indicators, specifically for air pollution, can be paired with demographic data to understand disproportionate exposures among minoritized and marginalized population subgroups.
Python-for-Geospatial-Analysis
My interactions with the course created by Tomas Beuzen, using Python to wrangle, plot, and model geospatial data using libraries such as geopandas, plotly, keplergl, and pykrige
Streamlit_deployment
Personal project, using Python to transform raw data stored across multiple tables, into key metrics and visualizations, filtered by user choice. Deployment in Streamlit app
Python_for_Spatial_Analysis
Basic programming concepts, libraries for spatial analysis, geospatial APIs and techniques for building spatial data processing pipelines
Mapping_and_data_viz_with_Python
My interactions with the course "A comprehensive guide for creating static and dynamic visualizations with spatial data" by Ujaval Gandhi
Geo_Data
My interactions with the Geographic Data Science book (link below) which serves as an introduction to a whole new way of thinking systematically about geographic data, using geographical analysis and computation to unlock new insights hidden within data.