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Subject
Artificial Intelligence

Program
BS CS

FinalTerm Exam- OnlineExam

Semester
Fall 2020

Date: 08-03-2021

Instructor
Engr.HasibShamshad Marks: 50

-Carefully read and Attempt All questions

-Once done rename your file as below and upload to portal:

FINALEXAM_CSIT_ ARTIFICIAL INTELLIGENCE _STUDENTNAME_Reg#

-Do not share your solved papers with anyone. In case the answers from two or more students are

identical then marks will be deducted for that answer.

Note: Do not copy sources from internet otherwise you will get zero marks.

Q1. In the context of Machine Learning explain the following in your own words.

1. Explain the purpose of this line in your own words?

–Type your answer here–

2. Supervised vs. Unsupervised Learning

–Type your answer here–

3. Classification vs. Regression

–Type your answer here–

4. Machine Learning vs. Statistics

–Type your answer here–

Q2. Import the relevant python package in Jupyter Notebook to make the following operations:

1. Make an array having 2 Rows & 4 Columns by using random numbers

2. Take the Transpose of this array

3. Take the Standard Deviation of this array

4. Take the Summation of this array

5. Find the Square root of this array

Attach your code screenshot here

Note: Solve this question in the jupyter Notebook, write your name as a comment in the beginning of your code. Take a screenshot of your code and paste it here as your answer. In case an array values found the same to other student array values, then both will get zero marks.

Q3. Download the csv file “Market_data” from the below link and do the following operations:

https://drive.google.com/file/d/1Xal_eKwWBL0otnd4dd41xVAf8hgANJRk/view?usp=sharing

1. Load/ Read this csv file in Jupyter Notebook

2. Make a scatter plot between “Milk” and “Grocery”

Attach your code screenshot here

Note: Solve this question in the jupyter Notebook, write your name as a comment in the beginning of your code. Take a screenshot of your code and paste it here as your answer.

Q4.

(a) The following table contains marks obtained by 10 students. Write the missing values by choosing random numbers between 0 and 100.

(b) Use this data set and list steps to execute any clustering technique to generate clusters.

Sr.

Marks

1

55

2

3

73

4

5

85

6

18

7

8

28

9

10

95

Hint: Apply the algorithm on this data until it converges.

Note: You will get zero marks if the table is found same with other student.

Q5. If we have 350000 training samples and Batch size is set to 50,000 then how many iterations it will take to complete 1 Epoch?

–Type your answer here–

Q6. Select a problem that has national significance and can be solved using a machine learning approach. Please make sure that you do not select a problem that is common, or it was used previously during the course as assignment or class exercise.

Please make sure that your answer does not contain any plagiarized content.

(a) Describe the problem in 150-250 words

(b) Describe why this problem is an important problem

(c) Describe why you think this problem can be solved using a machine learning approach.

(d) Which machine learning approach is better for this problem and why?

(e) List the sequence of steps that you would use in order to solve this problem using machine learning.

Q7. Download the csv file “Weather” from the below link

https://drive.google.com/file/d/1PDfHcCx9QnCPipvbXJJrAsD71x3XiKAG/view?usp=sharing

The dataset (csv file) contains information on weather conditions recorded on each day at various weather stations around the world. Information includes precipitation, snowfall, temperatures, wind speed etc. Predict the maximum temperature taking input feature as the minimum temperature.

· Use 80% data for training the model.

· Visualize the result by using a graph

Note: Solve this question in the jupyter Notebook, write your name as a comment in the beginning of your code. Take a screenshot of your code and paste it here as your answer.Also email me your code file to

hasib.csit@suit.edu.pk

Sarhad University of Science and Information Technology, Peshawar

Department of CS/IT

BS CS/SE

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