Question

Choose all that correct ( could be more than one answer):-

Q1) Which of the following best describes Deep Learning?
- Deep learning is a state of the art process for modeling predictive tasks of
extraordinary high dimensionality.
- Deep learning uses the Neural Network Algorithm to backpropogate across its

Q2) Which of these is a hyperparameter?
- Loss
- Learning rate
- Convergence
- Architecture

Q3) The following descriptions best describe what:
1. Value outputed from the training process.
2. Value estimated by the model.
3. Value not set by the ML practitioner.
- Dimensions
- Model Parameter
- Input noise
- Significance
- Model hyperparameter

Q4) "The following descriptions best describe what: 1. Value that has to be
assigned manually. 2. The K value in K-nearest-neighbore is an example of
this. 3. Value is set before the training."
- Model Parameter
- Model hyperparameter
- Significance
- Centroid
perceptrons.
- Deep learning is a modeling process that works particularly well for low
dimensionality problems.

Answer 1

Q1)deep learning is a state of art process for modeling predective tasks of extraordinry high dimensionality

Q2)Learning rate

Q3)

value estimated by the model --model hyperparameter

value not set by the ML practitioner --model parameter