Advanced Recurrent Neural Networks

Recurrent Neural Networks (RNNs) are used in all of the state-of-the-art language modeling tasks such as machine translation, document detection, sentiment analysis, and information extraction. Previously, we’ve only discussed the plain, vanilla recurrent neural network. We’ll be discussing state-of-the-art models that are used by companies like Google, Amazon, and Microsoft for language tasks. We’ll first … Read moreAdvanced Recurrent Neural Networks

Recurrent Neural Networks for Language Modeling

Many neural network models, such as plain artificial neural networks or convolutional neural networks, perform really well on a wide range of data sets. They’re being used in mathematics, physics, medicine, biology, zoology, finance, and many other fields. However, there is one major flaw: they require fixed-size inputs! The inputs to a plain neural network … Read moreRecurrent Neural Networks for Language Modeling

Using Neural Networks for Regression: Radial Basis Function Networks

Neural Networks are very powerful models for classification tasks. But what about regression? Suppose we had a set of data points and wanted to project that trend into the future to make predictions. Regression has many applications in finance, physics, biology, and many other fields. Radial Basis Function Networks (RBF nets) are used for exactly … Read moreUsing Neural Networks for Regression: Radial Basis Function Networks

Complete Guide to Deep Neural Networks – Part 2

Read Part 1 here. Last time, we formulated our multilayer perceptron and discussed gradient descent, which told us to update our parameters in the opposite direction of the gradient. Now we’re going to mention a few improvements on gradient descent and discuss the backpropagation algorithm that will compute the gradients of the cost function so … Read moreComplete Guide to Deep Neural Networks – Part 2

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