Deep Learning with Python (Video 18)

Deep Learning with Python (Video 18)

Assessment

Interactive Video

Information Technology (IT), Architecture, Social Studies

University

Hard

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The video introduces a challenge to design a deep learning model for automatic image captioning. It covers TensorFlow, a computational framework by Google, and discusses various datasets like Microsoft COCO and Flickr for training models. The video suggests using a combination of convolutional and recurrent neural networks to solve the image captioning problem. It provides hints and resources for learners to explore and encourages them to experiment with different approaches. The video concludes with a preview of the next topic, TensorFlow.

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5 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the main challenge proposed in the section regarding deep learning models?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

What are the two data sets mentioned that can be used for training image captioning models?

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

How does the convolutional neural network contribute to the image captioning process?

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

Describe the architecture suggested for the deep learning model in the video.

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5.

OPEN ENDED QUESTION

3 mins • 1 pt

What suggestions are provided for those who may get stuck while implementing the model?

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