Getting Started

This section provides step-by-step instructions to set up the Store Sales - Deep Learning Solution project on your local machine.

1. Clone the Repository

Clone the project from GitHub:

git clone https://github.com/yourusername/store-sales-DL.git cd store-sales-DL

2. Set Up a Python Environment

It is recommended to use a virtual environment:

python3 -m venv venv source venv/bin/activate

3. Install Dependencies

Install the required Python packages:

pip install -r requirements.txt

4. Download the Data

• Register and download the competition data from Kaggle Store Sales - Time Series Forecasting.
• Place all raw CSV files in the data/raw/ directory.

5. Run the Pipeline

You can run each step of the pipeline using Python scripts or the Makefile:

• Data Preparation:
  python store-sales-DL/dataset.py
  or
  make dataset

• Feature Engineering:
  python store-sales-DL/features.py
  or
  make features

• Model Training:
  python store-sales-DL/modeling/train.py
  or
  make train

• Model Inference:
  python store-sales-DL/modeling/predict.py
  or
  make predict

---

For more details on each step, refer to the corresponding sections in this documentation.