Deep Learning - Deep Neural Network for Beginners Using Python - Introduction to Course

Deep Learning - Deep Neural Network for Beginners Using Python - Introduction to Course

Assessment

Interactive Video

Information Technology (IT), Architecture

University

Hard

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The video tutorial introduces AI and deep learning solutions, focusing on perceptrons and their relation to the human brain. It covers linear and nonlinear solutions, logistic regression, and classification techniques. The course is divided into theory and practice using Python, with a focus on deep neural networks, including feed forward and backpropagation. The final project involves implementing a deep neural network using the IRIS dataset, with all necessary resources provided.

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5 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What are the similarities between the training of a perceptron and the training of a human child?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

Explain the importance of nonlinear solutions in deep learning.

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

What is logistic regression and how is it related to sigmoid functions?

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

What are the key components of a deep neural network and their functions?

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5.

OPEN ENDED QUESTION

3 mins • 1 pt

Describe the process of implementing a deep neural network from scratch.

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