Recommandation System
Project description
Hello World !! A Demo of Recomendation system Using SVD
How to work with ? Super easy !! First import our Library . import Tulips
#Then start set your ratings like this
#Rate(user_id,item_id,rating,time) Rate(1,3,5.0,’21-04-2022’)
#Then the magic word to recommend 10 items to your client
#TOP10(user_id) TOP10(1)
Demo :
import RecTulips as RS
RS.Rate(1,2,5,’10-04-2022 19:50:52’) RS.Rate(1,5,4,’30-03-2022 10:34:10’) RS.Rate(3,4,1,’11-03-2022 19:50:52’) RS.Rate(5,3,2,’12-04-2022 17:05:02’) RS.Rate(5,5,5,’22-04-2022 18:53:40’) RS.Rate(4,1,4,’25-04-2022 20:51:00’) RS.Rate(7,9,4,’20-04-2022 20:20:13’) RS.Rate(7,8,3,’25-03-2022 10:50:17’) RS.Rate(2,7,5,’15-04-2022 22:25:01’) RS.Rate(6,6,2,’21-04-2022 20:00:00’) RS.Rate(8,10,3,’20-04-2022 20:12:00’)
Result = RS.TOP10(2) # Will return the id of the 10 item recommended to user (2) print(Result) # [1, 9, 5, 10, 8, 4, 2, 6, 3]
Change Log
0.0.3 (12/06/2022)
Third Release Beta
We fix it to work with Firebase Database
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
File details
Details for the file RecTulips-0.0.3.tar.gz.
File metadata
- Download URL: RecTulips-0.0.3.tar.gz
- Upload date:
- Size: 3.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/34.0 requests/2.26.0 requests-toolbelt/0.9.1 urllib3/1.25.8 tqdm/4.56.0 importlib-metadata/4.8.3 keyring/23.4.1 rfc3986/1.5.0 colorama/0.4.4 CPython/3.6.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
65e20ef8bef945074472aba91292b379a66dfcff3946820d6783d39c9e00fcd8
|
|
| MD5 |
b8165e26cc074f2d793469731b793296
|
|
| BLAKE2b-256 |
2841801364a63675cf5eac1afa8a4591748e80c6e058bda01e05a0832c23937f
|