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1.
In Big Data, which of the following defines clique in a social network analysis?
2.
In social-network data analysis, the measure of a node centrality is calculated by the number of links. Which of the following properties does every node have?
3.
In Big Data, a small-scale model is expected to support millions of customers on a daily basis. Which of the following tasks is given the first priority?
4.
Which of the following statements represents a n-gram?
5.
What is the difference between Stochastic Gradient Descent and online learning?
6.
In Big Data, which of the following processes are flexible to parallelism in an ensemble model?
7.
In Big Data, which of the following defines the degrees of freedom problem?
8.
The marketing department of your company is looking for a way to call clients who are likely to churn and persuade them to stop. Which of these is the best way to build a model to accomplish this?
9.
In Big Data, which of these defines the Dirichlet distribution?
10.
You are trying to create a model of the prices of bikes at an auction. Though your model is trained well, why does it performs poorly on new data?