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NPTEL Python for Data Science Assignment 4 Answer

We Discuss About That NPTEL Python for Data Science Assignment 4 Answer

NPTEL Python for Data Science Assignment 4 Answer – Here All The Questions and Answers Provided to Help All The Students and NPTEL Candidate as a Reference Purpose, It is Mandetory to Submit Your Weekly Assignment By Your Own Understand Level.

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NPTEL Python for Data Science Assignment

ABOUT THE COURSE :
The course aims at equipping participants to be able to use python programming for solving data science problems.
INTENDED AUDIENCE : Final Year Undergraduates
PRE-REQUISITES : Knowledge of basic data science algorithms

INTENDED AUDIENCE B.E./Msc (Computer Science)

PRE-REQUISITES Good knowledge of C, Computer Organization and Architecture, x86 Assembly level programming.

Next Week Assignment Answers

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This course can have Associate in Nursing unproctored programming communication conjointly excluding the Proctored communication, please check announcement section for date and time. The programming communication can have a weightage of twenty fifth towards the ultimate score.

Final score = Assignment score + Unproctored programming exam score + Proctored Exam score
  • Assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
  • ( All assignments in a particular week will be counted towards final scoring – quizzes and programming assignments). 
  • Unproctored programming exam score = 25% of the average scores obtained as part of Unproctored programming exam – out of 100
  • Proctored Exam score =50% of the proctored certification exam score out of 100
YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF ASSIGNMENT SCORE >=10/25 AND
UNPROCTORED PROGRAMMING EXAM SCORE >=10/25 AND PROCTORED EXAM SCORE >= 20/50. 
If any one of the 3 criteria is not met, you will not be eligible for the certificate even if the Final score >= 40/100. 

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1. The power consumption of an individual house in a residential complex has been recorded for the previous year. This data is analysed to predict the power consumption for the next year. Under which type of machine learning problem does this fall under?

a. Classification
b. Regression
c. Reinforcement Learning
d. None of the above

Answer:- b
2. A dataset contains data collected by the Tamil Nadu Pollution Control Board on environmental conditions (154 variables) from one of their monitoring stations. This data is further analyzed to understand the most significant factors that affect the Air Quality Index. The predictive algorithm that can be used in this situation is ___________.

a. Logistic Regression
b. Simple Linear Regression
c. Multiple Linear Regression
d. None of the above

Answer:- c

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NPTEL Python for Data Science Assignment 4 Answers 2022
3. A regression model with the following function y = 60 + 5.2x was built to understand the impact of humidity (x) on rainfall (y). The humidity this week is 30 more than the previous week. What is the predicted difference in rainfall?

a. 156 mm
b. 15.6 mm
c. -156 mm
d. None of the above

Answer:- a
4. Which of the following machine learning techniques would NOT be appropriate to solve the problem given in the problem statement?

a. kNN
b. Random Forest
c. Logistic Regression
d. Linear regression

Answer:- d
5. The plot shown below denotes the percentage distribution of the target column values within the train_data dataframe. Which of the following options are correct?

NPTEL Python for Data Science Assignment 4 Answers 2022

a. Yes > 20, No > 60
b. No > 70, Yes > 20
c. Yes > 30, No > 70
d. Yes > 70, No > 30

Answer:- b
6. After applying logistic regression, what is/are the correct observations from the resultant confusion matrix?

a. True Positive = 29, True Negative = 94
b. True Positive = 94, True Negative = 29
c. False Positive = 5, True Negative = 94
d. None of the above

Answer:- b

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NPTEL Python for Data Science Assignment 4 Answers 2022
7. The logistic regression model built between the input and output variables is checked for its prediction accuracy of the test data. What is the accuracy range (in %) of the predictions made over test data?

a. 60 – 79
b. 90 – 95
c. 30 – 59
d. 80 – 89

Answer:- For Answer Click Here
8. How are categorical variables preprocessed before model building?

a. Standardization
b. Dummy variables
c. Correlation
d. None of the above

Answer:- b

9. A multiple linear regression model is built on the Global Happiness Index dataset “GHI_Report.csv”. What is the RMSE of the baseline model?

a. 2.00
b. 0.50
c. 1.06
d. 0.75

Answer:- c
10. X and Y are two variables that have a strong linear relationship. Which of the following statements are incorrect?

a. There cannot be a negative relationship between the two variables.
b. The relationship between the two variables is purely causal.
c. One variable may or may not cause a change in the other variable.
d. The variables can be positively or negatively correlated with each other.

Answer:- a, c

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