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advanced-analytics-and-statistical-concepts

Data analysis using Principal Component Analysis (PCA), Eigenvalues, Covariance matrix, Maximum Likelihood Estimation (MLE), ISOMAP, & Image recognition

city-planning-analysis-atl-food-scarcity-homelessness

customer-retention-using-ml-to-predict-churn

Ecommerce Customer Retention using Machine Learning: Predictive Analytics to Determine Customers Who May Churn

data-science-miscellaneous

AWS S3 & Sentiment Analysis, Basic Plotting with Matplotlib, & Supervised Learning & Machine Learning with Sklearn.

financial-model-analysis

Financial Models using advanced Excel spreadsheets, including: Three Statement Model Valuation; Financial Statement; Bond Duration, Convexity and Immunization; Valuation Capital Budgeting Model, Weighted Average Cost of Capital (WACC) & Sensitivity Analysis.

fire-2024

An urban fire risk prediction model using machine learning. Visualization of findings with map and table in interactive Streamlit app.

genai-blip

Bootstrapping Language-Image Pretraining (BLIP): Leverages both text and image data to enhance AI models' understanding and generation of image descriptions. It bridges the gap between natural language and visual content, or NLP & Computer Vision.

image-analysis-with-gaussian-mixture-model

Image analysis with Gaussian Mixture Model (GMM), with Principal Component Analysis (PCA) for dimensionality reduction of images prior to expectation-maximization (EM) algorithm implementation.

political-views-and-brain-composition-eda

Throughout this analysis, we will use various statistical approaches to visualize the relationship between the composition of of amygdala and acc levels in participants' brain and their political orientation: one and two dimensional histograms and kernel density estimator (KDE); scatter plots and line charts of the mean, variance, and skew based o