Skip to main content

Gumly

Project description

Gumly

APM

GAVB Utilities for Machine Learning Yum

The library consists of a collection of methods that can be used in order to help Data Scientists and Machine Learning Engineers during the development of Machine Learning applications seeking to reduce the time spent and complexity of coding.

Library Motivation and Description

During the development of ML projects at GAVB, Data Scientists have the necessity to code some features for projects repeatedly. So, MLOps area identified the opportunity to create some standard functions that can help as it can be used many times by data science area in each different project. Thus, it is possible to work with this framework that brings basically two main advantages: 1 - Projects executed in less time than usual, due to the code reusability; 2 - Establishment of a standard coding structure for projects.

Functionality

Value Validation

Dimensionality Reduction

Feature Engineering

Files

Hyperparameter Tuning

Metrics

How to install

pip install gumly

Release Notes

v1.0.0

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

gumly-1.0.1.tar.gz (11.4 kB view details)

Uploaded Source

Built Distribution

gumly-1.0.1-py3-none-any.whl (13.1 kB view details)

Uploaded Python 3

File details

Details for the file gumly-1.0.1.tar.gz.

File metadata

  • Download URL: gumly-1.0.1.tar.gz
  • Upload date:
  • Size: 11.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.1 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.10

File hashes

Hashes for gumly-1.0.1.tar.gz
Algorithm Hash digest
SHA256 ec8ef35a47e7b64e5dda89e9effb80d5a6d1bd02d19ea7f3269ced24bff68bca
MD5 e3e88346688322289f2f8d667af9dd36
BLAKE2b-256 8c96744f966890b10e38655e48c6a79f32be345044343b5a84091d00680e93dc

See more details on using hashes here.

File details

Details for the file gumly-1.0.1-py3-none-any.whl.

File metadata

  • Download URL: gumly-1.0.1-py3-none-any.whl
  • Upload date:
  • Size: 13.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.1 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.10

File hashes

Hashes for gumly-1.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 b9a76dc80cf507fae0883b84b71a1d10024a5945e795fec0a132a74c8cae9a60
MD5 777b0a2b540b23a70b5d51193c297aea
BLAKE2b-256 fa90bb5f54def566efc19ed9833dd39403eff62ac2a886d769dd74a32a17fc06

See more details on using hashes here.

Supported by

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