Live Output and Recommendation Overview
Live Output: News Recommendation System
After executing the notebook, the News Recommendation System successfully recommends news articles that are similar to the selected article. The recommendations are generated by comparing the textual content of every news article in the dataset.
Each stage of the project contributes to the final recommendation process.
Dataset Overview
Displays the structure of the HuffPost News Category Dataset, including the available columns and the total number of news articles.
Cleaned Dataset
Shows the processed dataset after removing missing values and duplicate records.
TF-IDF Feature Matrix
Displays the numerical representation of each news article after applying TF-IDF Vectorization.
Similarity Matrix
Generates similarity scores between all news articles using Cosine Similarity.
Recommended News Articles
Displays the top recommended news headlines that are most similar to the selected article.
Together, these outputs demonstrate how Machine Learning techniques can automatically recommend relevant news articles.










