AWS Certified Data Analytics Specialty 2021 - Hands-On! - Deep Learning 101

The video tutorial explores the intersection of deep learning and AWS, explaining the basics of neural networks and their biological inspiration. It covers artificial neurons, deep learning frameworks like TensorFlow and MXNet, and provides a code example. Different types of neural networks, such as CNNs and RNNs, are discussed, along with their applications. The tutorial concludes with guidance on deploying deep learning applications on AWS using EMR and EC2.

What is the primary inspiration behind the field of artificial intelligence?

• The behavior of animals

• The principles of physics

• The design of modern computers

• The structure of the human brain

How are neurons in the brain similar to processing units in a GPU?

• Both are involved in decision-making processes

• Both process information in parallel

• Both are responsible for storing data

• Both are used for long-term memory storage

What is the role of an activation function in an artificial neuron?

• To store data

• To connect neurons

• To sum up inputs

• To apply a transformation to the weighted sum

Which framework is NOT mentioned as a tool for developing deep neural networks?

• PyTorch

• Apache Spark

• MXNet

• TensorFlow

What type of neural network is specifically designed for image data processing?

• Long Short-Term Memory Network

• Convolutional Neural Network

• Recurrent Neural Network

• Feedforward Neural Network

Which AWS instance type is recommended for deep learning tasks?

• C5

• P3

• M5

• T2

What is the main advantage of using GPUs for deep learning?

• They are easier to program

• They have more storage capacity

• They can process multiple neurons in parallel

• They are cheaper than CPUs