Machine Learning Basics

What is machine learning ?

• Machine learning is the science of getting computers to act without being explicitly programmed.

• Machine Learning is a Form of AI that Enables a System to Learn from Data.

• Both A and B

• None of the above

Machine learning is an application of ___________.

• Blockchain

• Artificial Intelligence

• Both A and B

• None of the above

Example Application of Machine learning is __________.

• email filtering

• sentimental analysis

• face recognition

• All of the above

Machine learning approaches can be traditionally categorized into ______ categories.

• 7

• 4

• 5

• 3

The categories in which Machine learning approaches can be traditionally categorized are ______ .

• Supervised learning

• Unsupervised learning

• Reinforcement learning

• All of the above

_________ is the machine learning algorithms that can be used with labeled data.

• Regression algorithms

• Clustering algorithms

• Association algorithms

• All of the above

_________ is the machine learning algorithms that can be used with labeled data.

• Supervised learning

• Unsupervised learning

• Reinforcement learning

• All of the above

__________ is the machine learning algorithms that can be used with unlabeled data.

• Supervised

• Unsupervised

• Reinforcement learning

• all the above

__________ is the machine learning algorithms that can be used with unlabeled data.

• Regression algorithms

• Clustering algorithms

• Instance-based algorithms

• All of the above

The Real-world machine learning use cases are _______.

• Digital assistants

• Chatbots

• Fraud detection

• All of the above