Text Clustering with NLP and clustering techniques

Perform clustering techniques (K-Means and Hierarchical Clustering) on a food dataset to determine which types of food are more likely to be grouped together.

Step 1: Preprocess the data

• Remove punctuations, numbers, stop words
• Word stemming: words are reduced to their root form (plural to single)

Step 2: Create bag of words: Create a word matrix

Step 3: Apply TF-IDF on bag of words to evaluate how important a word is to a document in a collection or corpus.

K-Means Clustering

Hierarchical Clustering