You work for a hospital that is tracking the community spread of a virus. The hospital created a smartwatch application that uploads body temperature data from hundreds of thousands of participants. What is the best technique to analyze the data?

Many of the advances in machine learning have come from improved ___.

Naive Bayes looks at each _ predictor and creates a probability that belongs in each class.

Someone of your data science team recommends that you use decision trees, naive Bayes and K-nearest neighbor, all at the same time, on the same training data, and then average the results. What is this an example of?

Your data science team wants to use machine learning to better filter out spam messages. The team has gathered a database of 100,000 messages that have been identified as spam or not spam. If you are using supervised machine learning, what would you call this data set?

You work for a website that enables customers see all images of themselves on the internet by uploading one self-photo. Your data model uses 5 characteristics to match people to their foto: color, eye, gender, eyeglasses and facial hair. Your customers have been complaining that get tens of thousands of photos without them. What is the problem?

Which tools is used for processing, analyzing and visualizing the large data sets and can provide native support for Apache Spark distributed computing?

Which of the following defines the F-score measure to assess the quality of text retrieval?

In the SVM classif‌ication approach, which of the following options is used for solving the issue of the low-sparse SVM classifier?

In machine learning, which functions in the image is used to measure the size of vectors?

Which techniques can be used for solving the attribute conditional density estimation problem in the Bayesian Network classif‌ication method?