Deep Learning Concepts

What is the main concept that one should know according to learning objective 6.6?

• The importance of data preprocessing

• The underlying concept and methods for deep neural networks

• The history of neural networks

• The different programming languages used in deep learning

According to learning objective 6.7, what should one become familiar with?

• The practical applications of deep learning

• The different types of deep learning methods

• The mathematical theories behind deep learning

• The hardware requirements for deep learning

What should one understand about CNN, RNN, and LSTM as per learning objective 6.8?

• Their limitations and challenges

• How they are used in image processing

• How convolutional neural networks (CNN), recurrent neural networks (RNN), and long short-term memory networks (LSTM) work

• The programming languages used to implement these networks

What is the focus of learning objective 6.9?

• Understanding the ethical implications of deep learning

• Becoming familiar with the computer frameworks for implementing deep learning

• Learning about the data sets used in deep learning

• Studying the impact of deep learning on society

What foundational details are to be known as per learning objective 6.10?

• The foundational details about cognitive Computing and IBM Watson

• The history of IBM and its contributions to computing

• The details about cloud computing platforms

• The security aspects of cognitive computing

What is considered the newest member of the AI/Machine Learning family?

• Artificial Intelligence

• Machine Learning

• Deep Learning

• Neural Networks

What is one of the reasons for Deep Learning's superiority?

• Faster processing speed

• Automatic feature extraction and representation

• Larger data storage capacity

• Simpler algorithms

Which of the following is an example of AI and Machine Learning becoming a reality, as mentioned in the text?

• Time travel

• Siri, Google assistant, Alexa, Google home

• Flying cars

• Holographic displays

What is the relationship between Deep Learning, Machine Learning, and Artificial Intelligence according to the diagram?

• Deep Learning is a subset of Machine Learning, which is a subset of Artificial Intelligence.

• Machine Learning is a subset of Deep Learning, which is a subset of Artificial Intelligence.

• Artificial Intelligence is a subset of Machine Learning, which is a subset of Deep Learning.

• Machine Learning and Deep Learning are subsets of each other within Artificial Intelligence.

Which of the following is an example of a Deep Learning architecture mentioned in the diagram?

• Decision trees

• RNN

• Fuzzy logic

• Robotics