Answer:
Compare the predictions in terms of the predictors that were used, the magnitude of the difference between the two predictions, and the advantages and disadvantages of the two methods.
Our predictions for the two models were very simmilar. A difference of $32.78 (less than 1% of the total price of the car) is statistically insignificant in this case. Our binned model returned a whole number while the full model returned a more “accurate” price, but ultimately it is a wash. Both models had comparable accuracy, but the full regression seemed to be better trained. If we wanted to use the binned model I would suggest creating smaller bin ranges to prevent underfitting the model. However, when considering the the overall accuracy range and the car sale market both models would be
Explanation:
“Ana girl you need to stop going on the internet like that you know we can’t do that stuff on the work computers, and what if they check the history or the IT has that thing we’re you can see stuff on your computer on his computer?” ... “ Girl you finna get in some trouble and it’s gonna be your fault because you wanted Victoria Secret perfume” ... “Girl cut it out I’m telling you, and plus how do you know if I’m not IT I could like get you in trouble girl so yeah stop”
Answer is
productivity
Sometimes called the office or personal productivity software,
productivity software is dedicated to producing databases, spreadsheets,
charts, graphs, documents, graphs, digital video and worksheets. Reason behind
the name productivity is due to the fact that it increases productivity in
office work.
Answer:
Following are the correct python code to this question:
n1 = float(input('Input first number: '))#input first number
n2 = float(input('Input second number: '))#input second number
n3 = float(input('Input third number: '))#input third number
n4 = float(input('Input fourth number: '))#input fourth number
average = (n1+n2+n3+n4)/4 #calculate input number average
product = n1*n2*n3*n4 # calculate input number product
print('product: {:.0f} average: {:.0f}'.format(round(product),round(average))) #print product and average using round function
print('product: {:.3f} average: {:.3f}'.format(product,average)) #print product and average value
Output:
Please find the attachment.
Explanation:
The description of the above python code can be defined as follows:
- In the above python program four variable "n1, n2, n3, and n4" is defined, in which we take input from the user end, and in these user inputs we use the float method, that converts all the input value in to float value.
- In the next step, two variable average and product are defined, that calculate all input numbers product, average, and hold value in its variable.
- In the last line, the print method is used, which prints its variable value by using a round and format method.
Answer: Business intelligence
Explanation:
Most of the enterprises and organizations collects huge amount of data through the use of MIS. These data can be based on any aspect of the business. But the collection of such large sets of data is useless until and unless there is a business intelligence associated with it. the work of business intelligence is to use software tools for analysis of the collected data so that it could be useful for enterprise or company to look for patterns and trends in the market.
The outcome of such business intelligence is very helpful particularly to managers, executives for taking particular decisions in the greater interest of the company.
So we can say, business intelligence is an approach to boundary spanning that results from using sophisticated software to search through large amounts of internal and external data to spot patterns, trends, and relationships that might be significant.
