AI training-Phase 1-Day 1

What distinguishes AI from traditional computer programming?

• AI relies on human intervention, while traditional computer programming is fully automated.
• AI involves following a set of rules, while traditional computer programming involves trial and error.
• AI is limited to basic tasks, while traditional computer programming can handle complex problems.
• AI involves learning from data, while traditional computer programming involves explicit instructions.

Which application of AI is often used in object detection and facial recognition?

• NLP

• Computer Vision

• Supervised learning

• Unsupervised learning

What role does Machine Learning play in AI?

• Allowing machines to learn from data and improve over time

• Teaching machines to think independently without any input

• Programming machines to follow specific rules and instructions

• Programming machines to follow specific rules and instructions

Which AI sub-field is primarily focused on understanding and generating human language?

• Computer Vision

• Machine Learning

• NLP

• Speech

Which machine learning technique is often used to cluster unlabeled data based on similarities?

• Classification

• Regression

• Clustering

• Association rules

What is the difference between Machine learning and deep learning?

• Machine learning is a subset of artificial intelligence that involves training a model to make predictions based on data, while deep learning is a subset of machine learning that uses neural networks with multiple layers to learn representations of data.
• Machine learning uses classification, while deep learning uses regression

• Machine learning requires labeled data, while deep learning does not.
• Machine learning is used for image recognition, while deep learning is used for natural language processing.

What is the structure of a dataset in the context of AI?

• Hierarchical structure with parent-child relationships

• Tabular structure with rows as data points and columns as features

• Graphical structure with nodes and edges
• Sequential structure with time-series data

What is the difference between supervised learning and unsupervised learning?

• Supervised learning requires labeled data, while unsupervised learning does not.

• Supervised learning uses regression, while unsupervised learning uses classification.

• Supervised learning is used for clustering, while unsupervised learning is used for prediction.

• Supervised learning involves neural networks, while unsupervised learning involves decision trees.

Which machine learning technique is used to predict continuous values based on input data?

• Classification

• Regression

• Clustering

• Association rules

What is the primary goal of reinforcement learning in the context of AI?

• To classify data into different categories

• To predict future outcomes based on historical data

• To optimize decision-making based on rewards and penalties

• To identify patterns and relationships in data