Lecture 2
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Questions and Answers

What is the total number of layers in GoogLeNet?

22

How many network parameters are used in GoogLeNet?

7 million

What is the computation of GoogLeNet in MACs?

1.53G

What is the difference between Artificial Intelligence (AI) and Machine Learning (ML)?

<p>AI is the branch of computer science concerned with making computers or systems behave like humans, while ML is the branch of AI where algorithms learn and improve through the use of training data, rather than using explicit programming.</p> Signup and view all the answers

What is Deep Learning and how does it work?

<p>Deep Learning is a branch of machine learning that uses multiple layers of neural networks to process a given input, similar to the human brain.</p> Signup and view all the answers

What is PYNQ and how does it relate to Zynq?

<p>PYNQ is a Python Productivity for Zynq framework, specifically designed for the Zynq platform.</p> Signup and view all the answers

What is the purpose of training a machine learning model?

<p>The purpose of training a machine learning model is to develop a set of weights and biases that allow the model to make accurate predictions or estimates based on new observations.</p> Signup and view all the answers

What is the difference between training and inference in machine learning?

<p>Training refers to the process of developing a model by passing data through it and adjusting its weights and biases. Inference refers to using the trained model to predict or estimate outcomes from new observations.</p> Signup and view all the answers

What are the main components of a convolutional neural network (CNN)?

<p>The main components of a CNN are convolution layers, pooling layers, and fully connected layers. Convolution layers are responsible for detecting features in the input data, pooling layers reduce the dimensionality of the data, and fully connected layers perform the final classification or prediction.</p> Signup and view all the answers

What are some popular CNN architectures?

<p>Some popular CNN architectures include AlexNet, VGGNet, GoogleNet with Inception module, and Residual Network.</p> Signup and view all the answers

What is the difference between machine learning and deep learning?

<p>Machine learning is a subfield of artificial intelligence that involves designing a system that can learn, make decisions, and predict based on the given data set. Deep learning, on the other hand, is a branch of machine learning that uses multi-layer neural networks.</p> Signup and view all the answers

What are the three categories in which learning can be categorized?

<p>Learning can be categorized into supervised learning, semi-supervised learning, and unsupervised learning.</p> Signup and view all the answers

What is the purpose of training in machine learning?

<p>The purpose of training in machine learning is to tune a machine learning model to have better accuracy. It is an iterative process that minimizes the error function to increase accuracy.</p> Signup and view all the answers

What are convolutional neural networks (CNN) designed for?

<p>Convolutional neural networks (CNN) are designed to process images or pixel data. They use convolutional layers to convolve learned features with input data, making them well-suited for image processing.</p> Signup and view all the answers

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