A package for house price prediction pipeline.
Project description
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
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file house_prices_prediction_pipeline-0.3.2.3.tar.gz.
File metadata
- Download URL: house_prices_prediction_pipeline-0.3.2.3.tar.gz
- Upload date:
- Size: 3.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.9.19
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c4490c63000b9ddaaa0e99218227626a1c4d83134277d684018bd3901910601a
|
|
| MD5 |
2c8c084b55d31ad5bc4042bb090df040
|
|
| BLAKE2b-256 |
5283abeeb766ed0e52f26e644e42a915f9a8b25365c73ef714df9d76b3ebb017
|
File details
Details for the file house_prices_prediction_pipeline-0.3.2.3-py2-none-any.whl.
File metadata
- Download URL: house_prices_prediction_pipeline-0.3.2.3-py2-none-any.whl
- Upload date:
- Size: 5.9 kB
- Tags: Python 2
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.9.19
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
5c66c271a3e1d7d401ddb25691a58c7be157eda52cb0bad96115c507073c10dc
|
|
| MD5 |
63f529d62b746338e7d93c36605704be
|
|
| BLAKE2b-256 |
244644d886debc1d19b7d2f338ee1e9dc0a92b3294a4c0becbfcd0c001d3a4ae
|
