# Machine Learning and Deep Learning – Fundamentals and Applications | Week 1

**Session: JULY-DEC 2024**

**Course Name: Machine Learning and Deep Learning – Fundamentals and Applications**

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#### These are Machine Learning and Deep Learning Fundamentals and Applications Week 1 Assignment 1 Answers

**Q1. In a binary classification problem, the confusion matrix is a __ matrix.**

1×1

2×2

3×3

1×2

**Answer: Updating Soon (in progress)**

**Q2. Precision is defined as**

TP / (TP + TN)

TP / (TP + FN)

TP / (TP + FP)

TN / (TN + FP)

**Answer: Updating Soon (in progress)**

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**These are Machine Learning and Deep Learning Fundamentals and Applications Week 1 Nptel Assignment Answers**

**Q3. In a binary classification problem, a classifier correctly predicts 90 instances as positive, incorrectly predicts 15 instances as positive when they are negative, correctly predicts 90 instances as negative, and incorrectly predicts 10 instances as negative when they are positive. What is the accuracy of the classifier?**

80

85

87.8

95

**Answer: Updating Soon (in progress)**

**Q4. For the above question find the F1 score?**

78.2%

85%

87.8%

90.2%

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**These are Machine Learning and Deep Learning Fundamentals and Applications Week 1 Nptel Assignment Answers**

**Q5. Consider a dataset with actual values (Y) and predicted values (Y_pred) given below:Y = [5, 8, 12, 10, 15],Y_pred = [4, 7, 10, 11, 13].What is the bias of the model?**

0

-1

2.2

None of the above

**Answer: Updating Soon (in progress)**

**Q6. What is the variance of the model for the data given in the above question?**

0

-1

2.2

None of the above

**Answer: Updating Soon (in progress)**

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**These are Machine Learning and Deep Learning Fundamentals and Applications Week 1 Nptel Assignment Answers**

**Q7. Given X = {-2, -1, 0, 1, 2, 3, 4, 5, 6, 7} and the corresponding Y = {-0.5267, 1.3517, 3.8308, 5.5853, 7.5497, 9.9172, 11.2858, 13.7572, 15.7537, 17.3804}. Find the parameters of the linear regression model.**

2.0065, 4.0312

2.0065, 3.5722

1.9214, 3.5722

None of the above

**Answer: Updating Soon (in progress)**

**Q8. Find the MSE for the above question.**

0.05783

0.04247

0.04876

None of the above

**Answer: Updating Soon (in progress)**

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**Q9. A model with high variance and low bias means**

It can be too simple to understand the patterns of the data used in the training.

An excellent performance in the training data, but has a significant decrease in performance when evaluating the test data.

The model fits the test data better.

The model becomes less sensitive to the training data.

**Answer: Updating Soon (in progress)**

**Q10. Which of the following techniques is used to prevent overfitting in machine learning?**

To create complex machine learning models.

Train the model for more epochs.

Using a regularization to the model.

To increase the variance of the model.

**Answer: Updating Soon (in progress)**

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