A 30-year-old female patient is diagnosed with an uncomplicated urinary tract infection (UTI). The healthcare provider prescribes an oral antibiotic, nitrofurantoin (Macrobid), 100 mg to be taken twice daily for 7 days. Calculate the total amount of nitrofurantoin in milligrams (mg) administered to the patient over the entire course of treatment. (Round to the nearest whole number. Don’t enter units of measurement.)

Based on the above sentiment analysis, sentiment for document 1 is ____________________.

Which one is not true for lexicon-based sentiment analysis (i.e., dictionary-based sentiment analysis)?

An economist predicts consumer choice between banana (1) and apple (0) using two features (e.g., price and income) through the above artificial neural network. Based on the above figure, if the output of the sigmoid function in the output layer is 0.77, the consumer will purchase (1)____________ (a. banana, b. apple; 2 points). This example is a case of   (2) ___________(a. regression, b. binary classification, c. multi-class classification; 2 points). Here, the output of the sigmoid function in the output layer is the probability of y=1.

A 30-year-old female patient is diagnosed with an uncomplicated urinary tract infection (UTI). The healthcare provider prescribes an oral antibiotic, nitrofurantoin (Macrobid), 100 mg to be taken twice daily for 7 days. Calculate the total amount of nitrofurantoin in milligrams (mg) administered to the patient over the entire course of treatment. (Round to the nearest whole number. Don’t enter units of measurement.)

Based on the above sentiment analysis, sentiment for document 1 is ____________________.

We want to reduce the dimension of the original dataset from 4 dimensions (i.e., 4 variables) until the reduced dimensional dataset explains 69% of the total variance. Accordingly, based on the above PCA table, we need to select _____________.

Term frequency–inverse document frequency (TF-IDF):  TF-IDF = Term Frequency (TF) × Inverse document frequency (IDF)         = the frequency of the word `i` in the document `n` × log( ) Where N is the total number of documents and is the number of documents containing word `i`. For example, if there are two documents with three words as vocabulary, the TF-IDF embedding vector for each document is: Based on the above information, TF-IDF weights (1)_________(a. less b. more) frequency words in the given document, while (2)____________(a. less b. more) weights common words in documents.

Earnings per share (EPS) is $3.00 and shares outstanding are 80,000 and there are no preferred stocks issued by the company. What is net income?  

While receiving a report, the nurse learns that a client has hemiparesis. The nurse will plan care for this client based upon the understanding that the client has: