House Price Package
This package provides tools for predicting house prices. It includes modules for data preprocessing, model training, and making predictions.
Features
- Data Preprocessing: Clean and prepare your data for modeling.
- Model Training: Train machine learning models for house price prediction.
- Prediction: Make predictions on new data using the trained models.
Installation
You can install the package using pip. Make sure you have pip installed and updated:
pip install house-prices-prediction-pipeline
1 maintainer
Metadata
1 maintainer
Release files for house-prices-prediction-pipeline 0.3.2.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| house_prices_prediction_pipeline-0.3.2.3.tar.gz | 3.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| house_prices_prediction_pipeline-0.3.2.3-py2-none-any.whl | Python 2 | none | any | Details |
Total release size: 9.1 kB
Release files / house_prices_prediction_pipeline-0.3.2.3.tar.gz
| Download URL | house_prices_prediction_pipeline-0.3.2.3.tar.gz |
|---|---|
| Size | 3.2 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / house_prices_prediction_pipeline-0.3.2.3-py2-none-any.whl
| Download URL | house_prices_prediction_pipeline-0.3.2.3-py2-none-any.whl |
|---|---|
| Size | 5.9 kB |
| Tags | Python 2 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.9.19
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