News Recommendation System Overview

This Python code creates a news recommendation system based on the similarity of news article titles. Here's a brief overview:

1. Data Loading and Exploration

• Loads a dataset named 'News.csv' and explores its structure.

2. Data Visualization

• Visualizes the distribution of news categories using a bar plot.

3. Text Processing and Feature Extraction

• Extracts news article titles and converts them into numerical vectors using TF-IDF vectorization.

4. Similarity Computation

• Calculates cosine similarity between TF-IDF vectors of news titles.

5. Recommendation Function

• Defines a function to recommend news articles similar to a given title using cosine similarity scores.

6. Example Recommendation

• Provides an example recommendation based on the input news title: "Walmart Slashes Prices on Last-Generation iPads".

Conclusion

This code demonstrates the creation of a news recommendation system, which suggests similar news articles based on their titles.