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Wewaii [24]
3 years ago
10

With,user receive recommendations for items that are similar in type to items they already like.

Computers and Technology
1 answer:
Dennis_Churaev [7]3 years ago
6 0

Answer:

Collaborative filtering

Explanation:

This is one out of five on the Recommender system apart from most popular items, Association and Market Basket based Analysis, Content-based analysis, self and hybrid analysis where we use both content-based and collaborative based approach together. And the Recommender system is a very important topic in Data science. For this question, remember that Collaborative filtering focuses on user and various other user's choices which are mathematically alike to concerned users, and which we find with the study of a large data set. Thus, we can predict from our above study that what are going to be likes of concerned users, and at the item level, whether that item will be liked by the concerned user or not. And this is prediction, and we use this approach in Machine learning these days. For this question, and as mentioned in question the requirements, answer is Collaborative filtering.

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Who is katie and why is she deleting my answers
defon

Answer:

fr its so annoying when they delete your stuff when there is legit nothing wrong with the question

Explanation:

8 0
2 years ago
Read 2 more answers
Write a function maxTemp which takes a filename as string argument and returns the maximum temperature as float type for the wee
Alenkinab [10]

Answer:

#section 1

def maxTemp(filename):

   import pathlib

   f = pathlib.Path(filename)

   f.exists()

   if f.exists():

       f = open(filename, "r")

#section 2

       next(f)

       res = [int(sub.split(',')[1]) for sub in f]

       maxdata = (res[0])

       for i in range(len(res)-1):

           if maxdata < res[i]:

               maxdata = res[i]

       

       index = res.index(maxdata)

       f.close()

 #section 3  

       li = []  

       a = open(filename, "r")

       for line in a:

           line = line.strip()

           li.append(line)

   

       

       a.close()

       return (li[index+1])

   else:

       return -1

print(maxTemp("new.csv"))

Explanation:

#section 1:

The function maxTemp is defined. We import pathlib in other to check if the file exists, if it does we carry on with opening the file and if it doesn't the program returns -1.

#section 2:

We start splitting the sub-lists from the second line i.e <em>next(f)</em>. For each line we take the second index element and convert it to an integer.

<em>res = [int(sub.split(',')[1]) for sub in f] </em>

The maximum number is gotten by using the if statement to compare all elements in the list.  The index of the maximum item in the list is collected.

the file is then closed.

#section 3  :

The file is re-opened and all the lines are striped and passed into a new list and the index recovered from section 2, is used to get the day with the highest temperature and the line is returned.

8 0
3 years ago
Cloud suites are stored on your hard drive and are available anywhere you can access the Internet
puteri [66]
Is that a question or an answer... im confused?!?!

5 0
3 years ago
How many passes will it take to find the four in this list?
earnstyle [38]

Answer:

3 is the correct answer

I got correct on my test

7 0
3 years ago
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A manager would like information on the knowledge base searches conducted by customers and call center agents. Which two metrics
RideAnS [48]

Answer:

Option A and Option D are the correct options.

Explanation:

While any information is provided by the manager to its customers which is based on the knowledge of the search conducted.

So, the following knowledge is about the article of the lowest rating and about the search query that has no output.

  • Option B is not correct for the following scenario because the manager is informing about the searches conducted by customers, not for the data category.
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3 0
3 years ago
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