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

The video tutorial provides an overview of deep learning, explaining its biological inspiration from the human brain and how artificial neurons mimic this process. It discusses the role of GPUs in parallelizing neural network computations and introduces popular frameworks like TensorFlow and MXNet. The tutorial also covers different types of neural networks, such as feed-forward, convolutional, and recurrent networks, and their applications. Finally, it explains how to deploy deep learning applications on AWS using services like Elastic MapReduce and EC2.

What is the basic concept behind deep learning as it relates to neural networks?

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Explain how individual neurons in the brain function and how this relates to artificial neurons.

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What are the differences between feed forward neural networks and convolutional neural networks?

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Describe the role of GPU instances in deep learning applications on AWS.

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What is the significance of the term 'deep learning' in the context of neural networks?

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How do recurrent neural networks (RNNs) differ from traditional neural networks?

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What are some popular frameworks for developing deep neural networks?

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