Skip to content
#

nlp-keywords-extraction

Here are 254 public repositories matching this topic...

In today's financial market,news sentiment plays a crucial role in shaping investor behavior and influencing stock prices. By analyzing the sentiment behind stock-related news articles, investors can gain valuable insights to make informed trading decisions.We have performed sentiment analysis of the twitter data based on a whole day to analyse it.

  • Updated May 23, 2024
  • Jupyter Notebook

Our project uses a variety of machine learning and deep learning models to forecast supermarkets’ income for the following day based on a multitude of product categories. The main goal of our project is to use feature engineering techniques to improve forecasting accuracy.

  • Updated May 11, 2024
  • Jupyter Notebook

Named Entity Recognition with NER Dataset: Our project focuses on implementing Named Entity Recognition (NER) using a specialized NER dataset. Named Entity Recognition is a natural language processing (NLP) task that involves identifying and categorizing entities (such as names of persons, organizations, locations, etc.) within a body of text.

  • Updated May 7, 2024
  • Jupyter Notebook

Improve this page

Add a description, image, and links to the nlp-keywords-extraction topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the nlp-keywords-extraction topic, visit your repo's landing page and select "manage topics."

Learn more