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Test

Machine Leaning / AI

BHUPEN SHARMA 10 preguntas

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Preguntas del test (10)

  1. 1Which of the following statement(s) correctly represents a real neuron?
    1. AA neuron has a single input and a single output only
    2. BA neuron has multiple inputs but a single output only
    3. CA neuron has a single input but multiple outputs
    4. DA neuron has multiple inputs and multiple outputs
    5. EAll of these statements are valid
  2. 2A network is created when we multiple neurons stack together. Let us take an example of a neural network simulating an XNOR function.

    You can see that the last neuron takes input from two neurons before it. The activation function for all the neurons is given by:



    Suppose X1 is 0 and X2 is 1, what will be the output for the above neural network?    Imagen de la pregunta 2
    1. A0
    2. B1
  3. 3Which of the following statement(s) is / are true for Gradient Decent (GD) and Stochastic Gradient Decent (SGD)?

    1. In GD and SGD, you update a set of parameters in an iterative manner to minimize the error function.

    2. In SGD, you have to run through all the samples in your training set for a single update of a parameter in each iteration.

    3. In GD, you either use the entire data or a subset of training data to update a parameter in each iteration.
    1. AOnly 1
    2. BOnly 2
    3. COnly 3
    4. D1 and 2
    5. E2 and 3
    6. F1,2 and 3
  4. 4Which of the following is an example of a deterministic algorithm?
    1. APCA
    2. BK-MEANS
  5. 5A feature F1 can take certain value: A, B, C, D, E, & F and represents grade of students from a college.

    1) Which of the following statement is true in following case?
    1. AFeature F1 is an example of nominal variable.
    2. BFeature F1 is an example of ordinal variable.
    3. CIt doesn’t belong to any of the above category.
    4. DBoth of these
  6. 6Which of the following techniques perform similar operations as dropout in a neural network?
    1. ABagging
    2. BBoosting
    3. CStacking
  7. 7Which of the following gives non-linearity to a neural network?
    1. AStochastic Gradient Descent
    2. BRectified Linear Unit
    3. CConvolution function
    4. DNone of these
  8. 8In a neural network, which of the following techniques is used to deal with overfitting?
    1. ADropout
    2. BRegularization
    3. CBatch Normalization
    4. DAll of these
  9. 9For an image recognition problem (recognising a cat in a photo), which architecture of neural network would be better suited to solve the problem?
    1. AMulti Layer Perceptron
    2. BConvolutional Neural Network
  10. 10What is KNN and k-means clustering?
    1. AK-Nearest Neighbors is a supervised classification algorithm.
    2. Bk-means clustering is an unsupervised clustering algorithm
    3. CThe critical difference here is that KNN needs labeled points and is thus supervised learning, while k-means doesn’t — and is thus unsupervised learning.
    4. DAll of these

Información

Descripción
Test sobre Machine Leaning / AI, creado por BHUPEN SHARMA el 12/04/2018.
Idioma
English
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