深度学习第一周Introduction to Deep Learning习题整理
Introduction to Deep Learning,深度学习习题简介。
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Introduction to Deep Learning
- Which of the following best describes the role of AI in the expression “an AI-powered society”?
- Similar to electricity starting about 100 years ago, AI is transforming multiple industries.
- Through the “smart grid”, AI is delivering a new wave of electricity.
- AI runs on computers and is thus powered by electricity, but it is letting computers do things not possible before.
- AI is powering personal devices in our homes and offices, similar to electricity.
- Which of the following are reasons that didn’t allow Deep Learning to be developed during the '80s?
- The theoretical tools didn’t exist during the 80’s.
- Limited computational power.
- People were afraid of a machine rebellion.
- Interesting applications such as image recognition require large amounts of data that were not available.
- Recall this diagram of iterating over different ML ideas. Which of the statements below are true? (Check all that apply.)
- It is faster to train on a big dataset than a small dataset.
- Being able to try out ideas quickly allows deep learning engineers to iterate more quickly.
- Faster computation can help speed up how long a team takes to iterate to a good idea.
- Recent progress in deep learning algorithms has allowed us to train good models faster (even without changing the CPU/GPU hardware).
- Neural networks are good at figuring out functions relating an input xx to an output yy given enough examples. True/False?
- False
- True
- ReLU stands for which of the following?
- Representation Linear Unit
- Rectified Last Unit
- Rectified Linear Unit
- Recognition Linear Unit
- Images for cat recognition is an example of “structured” data, because it is represented as a structured array in a computer. True/False?
- True
- False
- A dataset is composed of age and weight data for several people. This dataset is an example of “structured” data because it is represented as an array in a computer. True/False?
- True
- False
- Why is an RNN (Recurrent Neural Network) used for machine translation, say translating English to French? (Check all that apply.)
- RNNs represent the recurrent process of Idea->Code->Experiment->Idea->…
- It is applicable when the input/output is a sequence (e.g., a sequence of words).
- It can be trained as a supervised learning problem.
- It is strictly more powerful than a Convolutional Neural Network (CNN).
- In this diagram which we hand-drew in the lecture, what do the horizontal axis (x-axis) and vertical axis (y-axis) represent?
答案:
x-axis is the amount of data(x轴是数据量) y-axis (vertical axis) is the
performance of the algorithm.(y轴(垂直轴)是算法的性能)
- Assuming the trends described in the previous question’s figure are accurate (and hoping you got the axis labels right), which of the following are true? (Check all that apply.)
- Decreasing the size of a neural network generally does not hurt an algorithm’s performance, and it may help significantly.
- Increasing the training set size generally does not hurt an algorithm’s performance, and it may help significantly.
- Increasing the size of a neural network generally does not hurt an algorithm’s performance, and it may help significantly.
- Decreasing the training set size generally does not hurt an algorithm’s performance, and it may help significantly.
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