Deep Learning - Artificial Neural Networks with Tensorflow - Outline

Deep Learning - Artificial Neural Networks with Tensorflow - Outline

Assessment

Interactive Video

Information Technology (IT), Architecture, Social Studies

University

Hard

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This course focuses on teaching Tensorflow 2 through an API-first, practice-oriented approach. While math is present, it is optional and meant to aid intuition. The course requires basic Python skills and familiarity with numpy and matplotlib. It covers machine learning concepts, including regression, classification, and neural networks, with optional sections on loss functions and gradient descent.

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3 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the significance of understanding the Tensorflow 2 API in this course?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

How can students fill in gaps in their knowledge during the course?

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the purpose of the optional sections on loss functions and gradient descent?

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