Link to the class room : https://www.coursera.org/learn/ai-for-everyone/lecture/74dmT/working-with-an-ai-team
Hi there greetings,
i would like to questions about training set and test set
from what i understand the training set team would have a harder task than test set team, the training set team would be preparing algorithm, dataset, while test set team just receive the already made algorithm, preparing data set and checking the accuracy and report back to the ai team
🏗️ Training Phase (Harder Job)
┌──────────────────────────────────────────┐
│ 
Collect and clean data │
│ 
Label data (Input A → Output B) │
│ 
Choose model & train it │
│ 
Tune parameters & optimize │
│ 
Finalize trained model 
│
└──────────────────────────────────────────┘
Model is now trained
🎯 Testing Phase (Easier Job)
┌──────────────────────────────────────────┐
│ Use trained model on new test data │
│ Measure accuracy and errors 
│
│ Report results to training team │
│ If bad accuracy, training team fixes │
│ Repeat with improved model │
└──────────────────────────────────────────┘
if this is true, how could this categorism is actually be made ? how is this fair ?