Deep Learning with Tensor Flow Free Certification

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Get Deep Learning with TensorFlowCertificate from MachineLearning.org.in which you can share in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents. 

Exam Details:

• Format: Multiple Choice Question
• Questions: 10
• Passing Score: 8/10 or 80%
• Language: English

Here are the Questions and Answers:

Question 1: When did deep learning start?

• 1943
• 1962
• 1978
• 1989

Question 2: Who is father of deep learning?

• Ilya Sutskever
• David Rumelhart
• Alex Krizhevsky
• Frank Rosenblatt

Question 3: How many layers Deep learning algorithms are constructed?

• 2
• 3
• 4
• 5

Question 4: Which of the following is a subset of machine learning?

• SciPy
• Numpy
• Deep Learning
• All of the above

Question 5: The Deep Learning first layer is called the?

• Hidden layer
• Outer layer
• Inner layer
• None of the above

Question 6: Assume that your machine has a large enough RAM dedicated to training neural networks. Compared to using stochastic gradient descent for your optimization, choosing a batch size that fits your RAM will lead to::

• a more precise but slower update.
• a less precise but faster update.
• a less precise and slower update.
• a more precise and faster update.

Question 7: Which of the following methods DOES NOT prevent a model from overfitting to the training set?

• Dropout
• Pooling
• Early stopping
• Data augmentation

Question 8: In which of the following applications can we use deep learning to solve the problem?

• Protein structure prediction
• Detection of exotic particles
• Prediction of chemical reactions
• All of the above

Question 9: Which of the following statements is true when you use 1×1 convolutions in a CNN?

• It can be used for feature pooling
• It can help in dimensionality reduction
• It suffers less overfitting due to small kernel size
• All of the above

Question 10: RNNs stands for?

• Recurrent Neural Networks
• Report Neural Networks
• Receives Neural Networks
• Recording Neural Networks

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