This project generates news headlines using a Long Short-Term Memory (LSTM) neural network.

Bunny Saini

Last update: Jan 24, 2022

Related tags

Deep Learning tensorflow keras text-generator lstm-neural-networks long-short-term-memory news-headline-generation

Overview

News Headlines Generator

bunnysaini/Generate-Headlines

Goal

This project aims to generate news headlines using a Long Short-Term Memory (LSTM) neural network working upon data collected (articles and comments) from the New York Times in 2020.

Dataset

The New York Times is one of the most popular online news platforms in the world. What sets the Times apart from other publications is the ability to engage and connect with its readers.This dataset contains all comments and articles from January 1, 2020 - December 31, 2020. The articles .csv file contains 16K+ articles with 11 features, and the comments .csv file contains nearly 5M comments with 23 features. https://www.kaggle.com/benjaminawd/new-york-times-articles-comments-2020

Libraries Used

Keras Library
Tensorflow

Result

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Owner

Bunny Saini

GitHub

The Dual Memory is build from a simple CNN for the deep memory and Linear Regression fro the fast Memory

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1 Jan 27, 2022

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Memory In Memory Networks It is based on the paper Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spati

12 May 30, 2022

This project generates news headlines using a Long Short-Term Memory (LSTM) neural network.

Related tags

Overview

News Headlines Generator

Goal

Dataset

Libraries Used

Result

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