Skip to main content

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


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

lib_ml_group3-0.3.6.tar.gz (3.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

lib_ml_group3-0.3.6-py3-none-any.whl (4.7 kB view details)

Uploaded Python 3

File details

Details for the file lib_ml_group3-0.3.6.tar.gz.

File metadata

  • Download URL: lib_ml_group3-0.3.6.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

Hashes for lib_ml_group3-0.3.6.tar.gz
Algorithm Hash digest
SHA256 f4bd4208cbfc9d92a2fbfe93b04c81f02e41ce9987992c82f33e763d80aba041
MD5 7df1ba70108737217094ecaf17c5bbff
BLAKE2b-256 1702ef47e05f88d6598aac8f5f72c7658fd4b3c3b060a3e4036ba300b85f5fc9

See more details on using hashes here.

File details

Details for the file lib_ml_group3-0.3.6-py3-none-any.whl.

File metadata

  • Download URL: lib_ml_group3-0.3.6-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

Hashes for lib_ml_group3-0.3.6-py3-none-any.whl
Algorithm Hash digest
SHA256 d3eb8483e6cc36d6230de982642fb051999b02f8a13abd8194712ed4a3e44e66
MD5 1d5958d7bafa6a175df6dd9c7a282e3d
BLAKE2b-256 35e79c2c9ff3e5980afb112df0d2d8f598041d79bd66f9c7e3b74074782c57d3

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page