A practical guide to RNN and LSTM in Keras

A practical guide to RNN and LSTM in Keras

After going through a lot of theoretical articles on recurrent layers, I just wanted to build my first LSTM model and train it on some texts! But the huge list of exposed parameters for the layer and the delicacies of layer structures were too complicated for me. This meant I had to spend a lot of time going through StackOverflow and API definitions to get a clearer picture. This article is an attempt to consolidate all of the notes which can accelerate the process of transition from theory to practice. The goal of this guide is to develop a practical understanding of using recurrent layers like RNN and LSTM rather than to provide theoretical understanding. For more in-depth understanding, I suggest this and this, which I recommend going through before reading this article. If you are ready, let’s get started!

Introduction

After going through a lot of theoretical articles on recurrent layers, I just wanted to build my first LSTM model and train it on some texts! But the huge list of exposed parameters for the layer and the delicacies of layer structures were too complicated for me. This meant I had to spend a lot of time going through StackOverflow and API definitions to get a clearer picture. This article is an attempt to consolidate all of the notes which can accelerate the process of transition from theory to practice. The goal of this guide is to develop a practical understanding of using recurrent layers like RNN and LSTM rather than to provide theoretical understanding.If you are ready, let’s get started!

Recurrent Neural Network

The complete RNN layer is presented as SimpleRNN class in Keras. Contrary to the suggested architecture in many articles, the Keras implementation is quite different but simple. Each RNN cell takes one data input and one hidden state which is passed from a one-time step to the next. The RNN cell looks as follows,

Image for post

The flow of data and hidden state inside the RNN cell implementation in Keras. Image by Author.

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Practice your skills in Data Science with Python, by learning and then trying all these hands-on, interactive projects, that I have posted for you.

Data Science Projects | Data Science | Machine Learning | Python

Practice your skills in Data Science with Python, by learning and then trying all these hands-on, interactive projects, that I have posted for you.

Data Science Projects | Data Science | Machine Learning | Python

Practice your skills in Data Science with Python, by learning and then trying all these hands-on, interactive projects, that I have posted for you.

Data Science Projects | Data Science | Machine Learning | Python

Practice your skills in Data Science with Python, by learning and then trying all these hands-on, interactive projects, that I have posted for you.