housing-price-prediction-NR 0.1.0

A package for predicting housing prices using machine learning models

Median housing value prediction

The housing data can be downloaded from https://raw.githubusercontent.com/ageron/handson-ml/master/. The script has codes to download the data. We have modelled the median house value on given housing data.

The following techniques have been used:

• Linear regression
• Decision Tree
• Random Forest

Steps performed

• We prepare and clean the data. We check and impute for missing values.
• Features are generated and the variables are checked for correlation.
• Multiple sampling techinuqies are evaluated. The data set is split into train and test.
• All the above said modelling techniques are tried and evaluated. The final metric used to evaluate is mean squared error.

To excute the script

python nonstandardcode.py

Installation

1. Clone the repository:

git clone https://github.com/yourusername/your-repo-name.git
cd your-repo-name

2. Setup conda environment

conda env create -f env.yaml

3. Activate the environment

conda activate myenv

4. Install the package

pip install -e .

Run tests - pytest tests/

5. Running the Code
## Running the Code

1. **Ingest Data:**

- Use the `ingest_data.py` script to download and create training and validation datasets.

```bash
python src/your_package/ingest_data.py --output ./data

2. Run the train.py script to train your model. 

python src/your_package/train.py --input ./data --output ./artifacts

3. Score the Model:

python src/your_package/score.py --model ./artifacts --data ./data --output ./results