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WorksheetsDeep Learning Quiz
Total questions: 12
Worksheet time: 7mins
What if the learning rate is too high?
Model is difficult to converge
Model consumes more computational resources
Model takes longer time to converge
Model is difficult to generalize
Which of the following is NOT supervised learning?
Decision Tree
Linear Regression
Naive Bayes
Clustering
A Machine Learning method that is concerned with how software agents should take actions in an environment is
Reinforcement learning
semi- supervised learning
unsupervised learning
supervised learning
What is the objective of backpropagation algorithm?
to develop learning algorithm for multilayer feedforward neural network
to develop learning algorithm for single layer feedforward neural network
to propagate the computed loss to compute gradient
all the mentioned
The algorithm creates a line or a hyperplane which separates the data into classes and also suitable for classification and regression
K-means clustering
Support vector machine
Bayesian inference
perceptron
___________uses the processing of the brain as a basis to develop algorithms that can be used to model complex patterns and prediction problems.
ANN
CNN
RNN
KNN
How many possible layers can be there in deep neural network
1
≥ 50
10
no limit
The number of nodes in the input layer is 10 and the hidden layer is 5. The maximum number of connections from the input layer to the hidden layer are
50
Less than 50
More than 50
It is an arbitrary value
In a simple MLP model with 8 neurons in the input layer, 5 neurons in the hidden layer and 1 neuron in the output layer. What is the size of the weight matrices between hidden output layer and input hidden layer?
[1 X 5] , [5 X 8]
[8 X 5] , [ 1 X 5]
[8 X 5] , [5 X 1]
[5 x 1] , [8 X 5]
The most suitable activation function for hidden layer
Sigmoid
Softmax
ReLu
tanh
__________________________ is a branch of machine learning that uses data, loads and loads of data, to teach computers how to do things only humans were capable of before.
Supervised Learning
Deep Learning
Unsupervised Learning
