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- 1. Multiple Choice
_________ type of model, the algorithm learns from a dataset which is labelled, and the algorithm uses the answer keys to evaluate its accuracy on the training data.
Supervised learning
UnSupervised learning
Reinforcement learning
- 2. Multiple Choice
In this type of model, the algorithms work towards accomplishing the goal or try to improve the performance in a particular task. This is used in gaming.
Reinforcement learning
Supervised Learning
UnSupervised Learning
- 3. Multiple Choice
•In this type of model, the algorithm learns and makes sense by extracting features/patterns from the unlabelled dataset provided (The system will evaluate by itself)
Unsupervised learning
supervised learning
Reinforcement learning
- 4. Multiple Choice
Information flows from
Input layer -> Hidden Layer-> Output layer
Feedforward Network
Backpropagation
- 5. Multiple Choice
Every Artificial Neural must have at least ______
two layers.
three layers.
four layers.
- 6. Multiple Choice
The neurons in the human brain regularly change their threshold.
True
False
- 7. Multiple Choice
The current Artificial Neural Networks are part of _____.
Weak Al systems.
Strong Al systems.
Future Al systems.
- 8. Multiple Choice
How many output layers are required for constructing an Artificial Neural Network?
1
3
2
- 9. Multiple Choice
Conventional Computing is deterministic in nature while Neural Computing is Probabilistic in nature.
True
False
- 10. Multiple Choice
Backpropagation calculates the ____ and propagates it back to earlier layers.
value
error
data
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