Gumly
Project description
Gumly
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
How to install
pip install gumly
Release Notes
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
Built Distribution
File details
Details for the file gumly-1.1.0.tar.gz
.
File metadata
- Download URL: gumly-1.1.0.tar.gz
- Upload date:
- Size: 14.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.13
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | aac19d576b6dc70ebaed8582a11fdd80ec329f650cfe336daa93dd1bfbd7a123 |
|
MD5 | c8310e5250582f479340adc65b5df26f |
|
BLAKE2b-256 | abf1424f9895df2cc72e0cd27e48397a6a727bf38a4757032c6c925aa3774958 |
File details
Details for the file gumly-1.1.0-py3-none-any.whl
.
File metadata
- Download URL: gumly-1.1.0-py3-none-any.whl
- Upload date:
- Size: 15.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.13
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 9b02cdb67dbb5d39847b33b654f71d6e81e61d56bf17aa926d8571c904dd019e |
|
MD5 | c003769a10ff0307b808f03d21622444 |
|
BLAKE2b-256 | 169064e1d2b3bd739eb2971bdd8e8f96d5dd2dc6788de7a4bd7c3419b7978fe0 |