6. Q3. What is true about Machine
Learning?
A)Machine Learning (ML) is that field of computer science.
B)ML is a type of artificial intelligence that extract patterns out of raw data
by using an algorithm or method.
C)The main focus of ML is to allow computer systems learn from experience
without being explicitly programmed or human intervention.
D)All of the above
7. Q3. What is true about Machine
Learning?
A)Machine Learning (ML) is that field of computer science.
B)ML is a type of artificial intelligence that extract patterns out of raw data
by using an algorithm or method.
C)The main focus of ML is to allow computer systems learn from experience
without being explicitly programmed or human intervention.
D)All of the above
8. Q4.Application of Machine learning
is _____.
A) email filtering
B) sentimental analysis
C) face recognition
D) All of the above
9. Q4.Application of Machine learning
is _____.
A) email filtering
B) sentimental analysis
C) face recognition
D) All of the above
10. Q5. The term machine learning
was coined in which year?
A)1958
B)1959
C)1960
D)1961
11. Q5. The term machine learning
was coined in which year?
A)1958
B)1959
C)1960
D)1961
12. Q6. The Real-world machine
learning use cases are _______.
A) Digital assistants
B) Chabot's
C) Fraud detection
D) All of the above
13. Q6. The Real-world machine
learning use cases are _______.
A) Digital assistants
B) Chabot's
C) Fraud detection
D) All of the above
14. Q7. Identify the type of learning
in which labeled training data is
used.
A) Unsupervised Learning
B) Supervised Learning
C) Semi unsupervised Learning
D) Reinforcement Learning
15. Q7. Identify the type of learning
in which labeled training data is
used.
A) Unsupervised Learning
B) Supervised Learning
C) Semi unsupervised Learning
D) Reinforcement Learning
16. Q8. Identify the successful
applications of ML.
A) Learning to classify new astronomical structures.
B) Learning to recognize spoken words.
C) Learning to drive an autonomous vehicle.
D) All of the above
17. Q8. Identify the successful
applications of ML.
A) Learning to classify new astronomical structures.
B) Learning to recognize spoken words.
C) Learning to drive an autonomous vehicle.
D) All of the above
