Deep Learning - Convolutional Neural Networks with TensorFlow - Outline

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Information Technology (IT), Architecture, Social Studies
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University
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Hard
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7 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the primary focus of this course?
Mathematical theory
API-first and practice-oriented learning
Hardware optimization for TensorFlow
Historical development of machine learning
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is NOT a prerequisite for this course?
Understanding of feed-forward ANN in TensorFlow 2
Basic Python programming skills
Ability to train and predict on tabular data sets
Advanced calculus knowledge
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the purpose of including math in this course?
To ensure students have a strong math background
To make the course more challenging
To focus solely on mathematical theory
To provide optional insight into how things work
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How should students view the prerequisites of the course?
As strict barriers to entry
As helpful tools for when they get stuck
As optional guidelines
As unnecessary requirements
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the first major topic covered in the course content?
Convolution in CNNs
Transfer learning
Recurrent neural networks
Data augmentation
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which technique allows leveraging pre-trained neural networks on different data sets?
Gradient descent
Transfer learning
Data augmentation
Batch normalization
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is a common misconception about NLP in deep learning?
It is only for text data
It is not applicable to CNNs
It requires large data sets
It can only be done with RNNs
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