A clustering based approach to inferring the use case of an intelligent contact. Developed by A3Data, packaged by D&A Research - Take Blip.

These details have not been verified by PyPI

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Project description

Intelligent Contact Use Case - by A3Data

This model returns the use case of an intelligent contact based on the messages exchanged via KMeans clustering.

These details have not been verified by PyPI

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

This version

0.0.3

Aug 16, 2022

0.0.2

Mar 1, 2022

0.0.1

Mar 1, 2022

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

Uploaded Aug 16, 2022 Source

Uploaded Aug 16, 2022 Python 3

Hashes for take-icusecases-0.0.3.tar.gz
Algorithm	Hash digest
SHA256	`ef347fbc8b58f386c4f565252736947cc9e55a31fb402a9512cbba6019afb9c1`
MD5	`7aad40cb16e9c531b630618e6815b0d3`
BLAKE2b-256	`6ea6ba9364a317c32d5c44ee7c034ed5b7d9908ff6617533e29e9f50aed65b1d`

Hashes for take_icusecases-0.0.3-py3-none-any.whl
Algorithm	Hash digest
SHA256	`930b9f1af77ccc643a8bd238f2c69c788314b58e679c74178cd2950b4a3e5a80`
MD5	`5dc3ee3a1e68e3f1d836ee23f402b79b`
BLAKE2b-256	`e746c817f7233ff8efbee6b519e275606315d3e5aae1df34f9abd2fdf79fbf39`