Under Construction
Demo
Under Construction
Training
Input Preparation
Dataset(Use flatten/normalized data)
Testing
Datasets collection
Description: This system uses the K-Means machine learning algorithm to create balanced player pairings.
It's an unsupervised method, which makes the setup process simple and fast.
Player data is pre-defined based on past performance, self-assessment, and/or other players' assessments.
b.Uploading csv files
To prepare your CSV file, first create it using the template provided in the tennis_player.csv file.
Name it as tennis_player.csv. Please take note that the uploaded CSV file will overwrite any existing files with the same name.
Evaluate the player's skill performance using a scale from 0 to 7, as illustrated in the example, template_skill_level.xlsx file
Upload the csv File
Status:
Pairing Process by AI
Ensure the file correctly uploaded , Press [RUN A.I.]
Demo
Under Construction
Training
Input Preparation
Dataset(Use flatten/normalized data)
Nos Layer
Nos Training/Iteration
Testing
Datasets collection
Under Construction
Demo
Under Construction
Training
Input Preparation
Dataset(Use flatten/normalized data)
Testing
Algo1 error reading:
Algo2 error reading:
Algo3 error reading:
Algo4 error reading:
Algo5 error reading:
Datasets collection
1.Object Detection - Tennis
a.Object Detection(1)
Click Here: Court View
b.Object Detection(2)
Click Here: Top View
2./etc
"Other MLs Algo"