Text Generation using LSTM

A Brief Introduction

LSTM short for Long Short-Term Memory is an Artificial Intelligence architecture. It is often used to build stable deep learning models. It can remember sequences in data elements that could be used to train models.

The model that I built uses LSTM architecture to remember the occurrence of words. It also tries to keep the meaning of the final generated text related to the seed sentence that we provide.

I used Tensorflow to train the model for the Text Generation process. It could also be used to train models for Digit Recognition, Image Recognition and other data-oriented NLP models.

Use and Work Procedure

For building this Text Generation Model I have used Tensorflow, Keras Library, Deep Learning process, NLP and LSTM. And by text generation, I mean by the process of generating a natural language having a sense of meaning. The model needs a see sentence based on which it would be able to Generate a complete summary.

Programming Languages Used

Python

Technology Used

Keras, Google Colab LSTM
Live Project / GitHub

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