A library for pre-processing data used in machine learning models
Project description
lib-ml
lib-ml is a Python library designed for preprocessing text data, especially tailored for machine learning applications. The library offers robust tools for tokenization, sequence padding, and label encoding, ensuring that text data is optimally prepared for model training and analysis. The library is available on PyPI and can be easily integrated into your projects.
Installation
Install lib-ml from PyPI:
pip install lib-ml-group3
Features
lib-ml includes the following features:
- Data Tokenization: Convert text into sequences of tokens or characters.
- Sequence Padding: Pad sequences to a uniform length to ensure consistency among data inputs.
- Label Encoding: Encode labels in a way that is suitable for machine learning models.
- Persistence: Save and load preprocessed data using Python's pickle module for easy reusability.
Usage
Here is a quick example of how to use lib-ml for text data preprocessing:
from lib_ml.preprocessing import preprocess_data
# Preprocess the data and save it to disk
preprocess_data()
The preprocess_data() function reads data from specified input directories, processes the text and labels, and saves the tokenized and encoded outputs to designated output directories.
License
lib-ml is open source software licensed as MIT.
Support
If you have any questions or issues with lib-ml, please open an issue on the project repository, and we will get back to you as soon as possible.
Project details
Release history Release notifications | RSS feed
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 lib_ml_group3-0.3.3.tar.gz.
File metadata
- Download URL: lib_ml_group3-0.3.3.tar.gz
- Upload date:
- Size: 3.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.8.3 CPython/3.9.19 Linux/6.5.0-1022-azure
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
e3f553e8954ebee16a010a7ffa2166d8ac65e485ae7f6734e9fa007bccdbc2f9
|
|
| MD5 |
94cb82da3187ebcd82c5c8002eb64a98
|
|
| BLAKE2b-256 |
cbcbf624e6d3dc9fa902756fb6cd9e8277f66649a54c0424c3265e52a9db30bd
|
File details
Details for the file lib_ml_group3-0.3.3-py3-none-any.whl.
File metadata
- Download URL: lib_ml_group3-0.3.3-py3-none-any.whl
- Upload date:
- Size: 4.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.8.3 CPython/3.9.19 Linux/6.5.0-1022-azure
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
ad5362b10408f0d6c93ec8b679301338624f7385a6d58233a5bb1e22fd5065e2
|
|
| MD5 |
d8beb261bd235c288fd55615e7d7e19e
|
|
| BLAKE2b-256 |
93f1e3b3ca6be2d1ecd5cdfe834a01ddc26c9733ef85906a17716ee8a31395ec
|