Answer:
AspNet.ScriptManager.jQuery?
Explanation:
Unobtrusive validation means we can perform a simple client-side validation without writing a lot of validation code by adding suitable attributes and also by including the suitable script files. 
One of the benefits of using a unobtrusive validation is that it help to reduce the amount of the Java script that is generated. We can install the AspNet.ScriptManager.jQuery? for the unobtrusive validation. 
When the unobtrusive validation is used, validation of the client is being performed by using a JavaScript library. 
 
        
             
        
        
        
Answer:
Following are the code in the PHP Programming Language:
<u>foreach ($country_codes as $code => $name) {
</u>
Explanation:
The following option is true because the Foreach statement only works on the objects and array and this statement is good for accessing the key and value pairs from the array.
So, that's why to print following associative array through echo statement we use the Foreach loop statement with following right condition.
<u>syntax</u>:
foreach (array as value)
{
   code or body to execute;
}
 
        
             
        
        
        
Text = “ I really like owls. Did you know that an owls eyes are more than twice as big as the eyes of other birds of comparable weight? And that when an owl partially closes its eyes during the day, it is just blocking out light? Sometimes I wish I could be an owl.
word = ‘owl’
texts = text.lower()
owlist = list(texts.split())
count = text.count(word)
num = [owlist, count] #num has no meaning just random var
print(num)
Alter in anyway you want so that you can succeed. ✌
        
             
        
        
        
Answer:
Chech the explanation
Explanation:
<em>In [16]:</em>
<em />
# Your answer to this question might be written on more than a line. 
datascience_trials = make_array() 
for  i  in np.arange(1000): 
             datascience_trials = np.append(datascience_trials, simulate_several_key_strikes(1)) 
datascience_proportion = np.count_nonzero(datascience_trials == 'datascience')/1000 
datascience_proportion
<em>Out [16]:</em>
0.0
<em>In [17]:</em>
_ = ok.grade('q2_4')
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#Running tests
 
        
             
        
        
        
3-D prosthetics would most likely be the answer, also, don’t copy links it’s most likely not the answer anyways.