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Artificial Intelligence

Unit 1

Optimization

Introduction to Optimization Gradient Descent Stochastic Gradient Descent Adam Optimization

Unit 2

Neural Networks

Introduction to Neural Networks Feedforward Neural Networks Convolutional Neural Networks Recurrent Neural Networks

Unit 3

Backpropagation

Introduction to Backpropagation Backpropagation in Neural Networks

Unit 2 • Chapter 4

Recurrent Neural Networks

Video Summary

Recurrent Neural Networks (RNNs) are a type of neural network that is designed to process sequential data. They are used in a wide variety of applications, such as natural language processing, speech recognition, and machine translation. RNNs work by maintaining a hidden state that is updated as new data is processed. This allows them to learn long-term dependencies in the data, which is important for tasks such as language processing.

Knowledge Check

What is the main difference between a recurrent neural network and a feedforward neural network?

Recurrent neural networks use backpropagation through time, while feedforward neural networks do not

Recurrent neural networks use a single hidden layer, while feedforward neural networks use multiple hidden layers

Recurrent neural networks are trained on time-series data, while feedforward neural networks are not

Recurrent neural networks are more computationally expensive than feedforward neural networks

What is the vanishing gradient problem?

A problem that occurs when training recurrent neural networks with backpropagation through time, where the gradients become smaller and smaller as the network goes deeper

A problem that occurs when training recurrent neural networks with backpropagation through time, where the gradients become larger and larger as the network goes deeper

A problem that occurs when training recurrent neural networks with backpropagation through time, where the gradients become more and more volatile

A problem that occurs when training recurrent neural networks with backpropagation through time, where the gradients become more and more stable

What are some common applications of recurrent neural networks?

Natural language processing

Speech recognition

Machine translation

Image classification

Object detection

Artificial Intelligence

Recurrent Neural Networks

Video Summary

Knowledge Check

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Introduction to Backpropagation

Convolutional Neural Networks