AI & ML Concepts

What is a neural network?

• A neural network is a type of computer hardware used for data storage.

• A neural network is a type of weather pattern associated with hurricanes.

• A neural network is a series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates.

• A neural network is a type of plant species found in tropical regions.

Explain the concept of deep learning.

• Deep learning uses only one layer of neural networks

• Deep learning is not related to machine learning

• Deep learning is a type of shallow learning

• Deep learning is a subset of machine learning using neural networks with multiple layers to learn complex patterns in data.

What is Natural Language Processing (NLP) used for?

• Natural Language Processing (NLP) is used for analyzing, understanding, and generating human language data.

• Natural Language Processing (NLP) is used for weather forecasting.

• Natural Language Processing (NLP) is used for car maintenance.

• Natural Language Processing (NLP) is used for cooking recipes analysis.

How is Computer Vision applied in artificial intelligence?

• Computer Vision is used in AI for natural language processing

• Computer Vision is used in AI for sentiment analysis

• Computer Vision is used in AI for speech recognition

• Computer Vision is used in AI for tasks like image recognition, object detection, facial recognition, and image segmentation.

Define Reinforcement Learning and provide an example.

• Reinforcement Learning is a type of machine learning where an agent learns to make decisions by interacting with an environment. An example is training a computer program to play chess.

• An example of Reinforcement Learning is predicting stock prices

• Reinforcement Learning involves only static datasets

• Reinforcement Learning is a type of supervised learning

Differentiate between supervised and unsupervised learning.

• Supervised learning uses labeled data, while unsupervised learning uses unlabeled data.

• Supervised learning uses unlabeled data, while unsupervised learning uses unlabeled data.

• Supervised learning uses labeled data, while unsupervised learning uses labeled data.

• Supervised learning uses unlabeled data, while unsupervised learning uses labeled data.

Discuss the history of artificial intelligence.

• The history of artificial intelligence is limited to the last decade

• Artificial intelligence has always been a widely accepted field with no controversies

• Artificial intelligence was first developed in the 1800s

• The history of artificial intelligence dates back to ancient civilizations, with the modern field beginning in the 1950s and experiencing periods of growth and decline.

What are the main goals of artificial intelligence?

• Data visualization, social media marketing, virtual reality

• Automation, decision-making, problem-solving, learning, natural language processing

• E-commerce, digital marketing, mobile app development

• Cloud computing, blockchain technology, cybersecurity

How are neural networks trained?

• Neural networks are trained by setting all weights to the same value.

• Neural networks are trained using backpropagation to adjust weights based on error between predicted and actual outputs.

• Neural networks are trained using reinforcement learning exclusively.

• Neural networks are trained by randomly adjusting weights without considering error.

What is the role of activation functions in deep learning?

• Activation functions introduce non-linearity to the neural network, allowing it to learn complex patterns and relationships in the data.

• Activation functions smooth out the data distribution in deep learning models.

• Activation functions are only used in shallow learning, not deep learning.

• Activation functions reduce the number of layers in a neural network.