Machine Learning with Python Free Certificate

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Get Machine Learning with Python Certificate from MachineLearning.org.in which you can share in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents. 

Exam Details:

• Format: Multiple Choice Question
• Questions: 10
• Passing Score: 8/10 or 80%
• Language: English

Here are the Questions and Answers:

Question 1: What is Machine Learning?

• The autonomous acquisition of knowledge through the use of manual programs
• The selective acquisition of knowledge through the use of manual programs
• The autonomous acquisition of knowledge through the use of computer programs
• The selective acquisition of knowledge through the use of computer programs

Question 2: How many types of Machine Learning Techniques?

• 3
• 5
• 7
• 9

Question 3: Machine Learning is a field of AI consisting of learning algorithms that_________

• At executing some task
• Over time with experience
• Improve their performance
• All of the above

Question 4: In Model based learning methods, an iterative process takes place on the ML models that are built based on various model parameters, called?

• Mini-batches
• Hyperparameters
• Superparameters
• Optimizedparameters

Question 5: Which of the following is a widely used and effective machine learning algorithm based on the idea of bagging?

• Random Forest
• Regression
• Classification
• Decision Tree

Question 6: Which of the following statements about regularization is not correct?

• Using too large a value of lambda can cause your hypothesis to overfit the data
• Using too large a value of lambda can cause your hypothesis to underfit the data.
• Using a very large value of lambda cannot hurt the performance of your hypothesis.
• None of the above

Question 7: Data points have negative residual

• If they are below the regression line
• If they are above the regression line
• If the regression line actually passes through the point
• None of the above

Question 8: In linear regression, we try to __ the least square errors of the model to identify the line of best fit.

• Change
• Maximize
• Minimize
• None of the above

Question 9: Which of the following evaluation metrics can be used to evaluate a model while modeling a continuous output variable?

• Logloss
• Accuracy
• AUC-ROC
• Mean-Squared-Error

Question 10: Which of the following is not a supervised learning?

• PCA
• Naive Bayesian
• Linear Regression
• Decision Tree

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