AI Worksheet: Training Data, Model, Prediction
AI tip (Data → model → prediction): Training data = the examples (500 labelled leaf photos, old emails marked spam). The model = the learned patterns that training builds. A prediction = the model’s answer about something NEW (naming a new leaf, flagging a new email). The order is always data → model → prediction.
NameDateTime takenScore ___ / 40
- 1.⏩ In machine learning, which comes first: recorded spoken words or naming a new leaf? (a) recorded spoken words (b) naming a new leaf
- 2.⏩ In machine learning, which comes first: typing a new spoken word or what training builds? (a) typing a new spoken word (b) what training builds
- 3.Which of these is training data? (a) tomorrow’s rain guess (b) what training builds (c) past weather records (d) naming a new leaf
- 4.Which of these is the model? (a) the learned patterns (b) naming a new leaf (c) old emails marked spam (d) flagging a new email
- 5.Which of these is a prediction? (a) labelled fruit photos (b) past weather records (c) the trained program (d) naming a new fruit photo
- 6.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
- 7.Which of these is training data? (a) what training builds (b) 500 labelled leaf photos (c) naming a new fruit photo (d) the trained program
- 8.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
- 9.True or false: “the learned patterns” is training data. (a) False (b) True
- 10.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) a prediction (c) training data
- 11.⏩ In machine learning, which comes first: typing a new spoken word or recorded spoken words? (a) typing a new spoken word (b) recorded spoken words
- 12.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) training data (c) a password (d) a label error
- 13.True or false: “naming a new leaf” is a prediction. (a) True (b) False
- 14.Which of these is training data? (a) the trained program (b) labelled fruit photos (c) tomorrow’s rain guess (d) the learned patterns
- 15.⏩ In machine learning, which comes first: the learned patterns or tomorrow’s rain guess? (a) the learned patterns (b) tomorrow’s rain guess
- 16.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True
- 17.⏩ In machine learning, which comes first: old emails marked spam or naming a new leaf? (a) old emails marked spam (b) naming a new leaf
- 18.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) the model (c) training data
- 19.🔁 What is the right order? (a) prediction, data, model (b) model, prediction, data (c) data, prediction, model (d) data, model, prediction
- 20.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) a prediction (c) the model
- 21.True or false: “tomorrow’s rain guess” is training data. (a) False (b) True
- 22.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) training data (c) a prediction
- 23.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) a prediction (c) the model
- 24.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) training data (c) the model
- 25.Which of these is the model? (a) flagging a new email (b) typing a new spoken word (c) naming a new fruit photo (d) the trained program
- 26.⏩ In machine learning, which comes first: naming a new fruit photo or past weather records? (a) naming a new fruit photo (b) past weather records
- 27.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
- 28.True or false: “recorded spoken words” is training data. (a) True (b) False
- 29.Which of these is training data? (a) old emails marked spam (b) flagging a new email (c) naming a new fruit photo (d) the learned patterns
- 30.True or false: “the trained program” is the model. (a) False (b) True
- 31.⏩ In machine learning, which comes first: the trained program or tomorrow’s rain guess? (a) the trained program (b) tomorrow’s rain guess
- 32.⏩ In machine learning, which comes first: 500 labelled leaf photos or naming a new leaf? (a) 500 labelled leaf photos (b) naming a new leaf
- 33.🧪 Why test a model on NEW examples? (a) to make it slower (b) to delete its data (c) to change its name (d) to see if it works
- 34.Which of these is training data? (a) flagging a new email (b) naming a new leaf (c) the learned patterns (d) recorded spoken words
- 35.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) training data (c) the model
- 36.📦 What happens during training? (a) it takes photos (b) it learns patterns (c) it prints labels (d) it charges up
- 37.Which of these is a prediction? (a) the learned patterns (b) the trained program (c) tomorrow’s rain guess (d) past weather records
- 38.⏩ In machine learning, which comes first: naming a new fruit photo or 500 labelled leaf photos? (a) naming a new fruit photo (b) 500 labelled leaf photos
- 39.True or false: “naming a new fruit photo” is a prediction. (a) True (b) False
- 40.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) a prediction (c) training data
Answer key
- recorded spoken words
- what training builds
- past weather records
- the learned patterns
- naming a new fruit photo
- True
- 500 labelled leaf photos
- training data
- False
- a prediction
- recorded spoken words
- a prediction
- True
- labelled fruit photos
- the learned patterns
- True
- old emails marked spam
- training data
- data, model, prediction
- training data
- False
- a prediction
- training data
- the model
- the trained program
- past weather records
- 500 labelled leaf photos
- True
- old emails marked spam
- True
- the trained program
- 500 labelled leaf photos
- to see if it works
- recorded spoken words
- training data
- it learns patterns
- tomorrow’s rain guess
- 500 labelled leaf photos
- True
- the model
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