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https://github.com/saminegash/sales-prediction-using-mlmodel
Business Need: Rossmann Pharmaceuticals needs data scientist since their finance team wants to forecast sales in all their stores across several cities six weeks ahead of time. Managers in individual stores rely on their years of experience as well as their personal judgement to forecast sales. The data team identified factors such as promotions, competition, school and state holidays, seasonality, and locality as necessary for predicting the sales across the various stores and my job is to build and serve an end-to-end product that delivers this prediction to Analysts in the finance team.
https://github.com/saminegash/sales-prediction-using-mlmodel
data-wrangling exploratory-data-analysis flask machine-learning pandas pipeline python3 random-forest seaborn
Last synced: 3 days ago
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Business Need: Rossmann Pharmaceuticals needs data scientist since their finance team wants to forecast sales in all their stores across several cities six weeks ahead of time. Managers in individual stores rely on their years of experience as well as their personal judgement to forecast sales. The data team identified factors such as promotions, competition, school and state holidays, seasonality, and locality as necessary for predicting the sales across the various stores and my job is to build and serve an end-to-end product that delivers this prediction to Analysts in the finance team.
- Host: GitHub
- URL: https://github.com/saminegash/sales-prediction-using-mlmodel
- Owner: saminegash
- Created: 2020-08-20T03:47:34.000Z (about 4 years ago)
- Default Branch: master
- Last Pushed: 2020-08-28T02:25:57.000Z (about 4 years ago)
- Last Synced: 2024-06-29T13:29:23.749Z (5 months ago)
- Topics: data-wrangling, exploratory-data-analysis, flask, machine-learning, pandas, pipeline, python3, random-forest, seaborn
- Language: Jupyter Notebook
- Homepage:
- Size: 18.5 MB
- Stars: 1
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: ReadME.md
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README
# Sales Prediction using Machine learning
> This repository contains all code, saved models and plots used in the 10Academy Challange of Week 5.
The Rossmann Store Sales problem is a [Kaggle Competition](https://www.kaggle.com/c/rossmann-store-sales). The challenge requires participants to forecast sales of Rossmann over a period of 6 weeks given historical data of 1,115 stores located across Germany.
All code for this project is written in [Python 3](https://www.python.org/downloads/). The list of dependencies can be found in `requirements.txt`. To set up your development environment, navigate to this repository and run the following on a terminal:
```
$ pip install -r requirements.txt
```
The `data/` directory contains all data files downloaded from Kaggle. The all output files are recorded in the `predictions/` directory.
## Running