data-science-portfolio

U.S. Retail Sales Forecasting

Status: Case study summary • Repo: data-science-portfolio • Notebook: see repo’s notebooks/

Problem

Briefly state the business or research question in one paragraph. What decision does this analysis inform?

Data

Source: Describe where the data came from and the time range.
Shape: Rows × columns, frequency, any joins.
Prep: Cleaning, feature engineering, handling missing values/outliers.

Methods

Summarize your approach (algorithms, libraries, evaluation setup). Keep this terse; link to code for detail.

Results

Bullet or short paragraph with primary outcomes (e.g., RMSE = X on a fixed holdout; top topics; key segments). Add one small table or figure if helpful.

What it means

Translate results into plain English implications for a stakeholder (ops, marketing, policy).

Reproduce

Clone repo
Create environment and install dependencies
Run notebook(s) or python -m src.train