Machine Learning with Python Free Certificate

Related Articles

Field Sales Trainee Hiring by Swiggy | Swiggy Jobs | Swiggy Internships

10 hours ago

IBM SkillsBuild Training Program | Google Career Certificate Scholarship Program

1 day ago

Infosys Springboard Fundamentals of Information Security Free Certification Program

2 days ago

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

CLICK HERE TO APPLY FOR THE QUIZ: CLICK HERE