Recommendation-System

A recommendation system is a type of software that suggests items to users based on their preferences, past behavior, and other relevant data.

Topics Covered

The topics that will be covered or included in this repository:

Case 1: it recommendes on the basis of popularity, for the customers that are new and we have no data about them.
Case 2 : Cluster based recommendation system
Case 3 : Collaborative filtering
Case 4 : Frequently bought together (No ML): It suggests items that customers purchase in bulk.The tactic I employed in this case was to filter out products with the same ID and the date those items were, of course, purchased simultaneously. I then developed a frequency table to recommend the top items that were purchased concurrently.
Market Basket analysis: uses apriori algorithm for recommendation.

The examples in this repository are primarily implemented in Python, and require the following dependencies:

Name		Name	Last commit message	Last commit date
Latest commit History 48 Commits
1st case Based on popularity .ipynb		1st case Based on popularity .ipynb
2nd Case ( Cluster recommendation and word redundancy based analysis).ipynb		2nd Case ( Cluster recommendation and word redundancy based analysis).ipynb
3rd case Collaborative filtering (Pearson Co-relation).ipynb		3rd case Collaborative filtering (Pearson Co-relation).ipynb
4th case Self created -Frequently bought together system(No ML).ipynb		4th case Self created -Frequently bought together system(No ML).ipynb
ANALYSIS WITH VISUALIZATION PRT-1.ipynb		ANALYSIS WITH VISUALIZATION PRT-1.ipynb
ANALYSIS WITH VISUALIZATION PRT-2.ipynb		ANALYSIS WITH VISUALIZATION PRT-2.ipynb
ANALYSIS WITH VISUALIZATION PRT-3.ipynb		ANALYSIS WITH VISUALIZATION PRT-3.ipynb
ANALYSIS WITH VISUALIZATION PRT-4.ipynb		ANALYSIS WITH VISUALIZATION PRT-4.ipynb
Market Basket.ipynb		Market Basket.ipynb
README.md		README.md
TF-IDF VECT.ipynb		TF-IDF VECT.ipynb
model_cluster_recommend.pickle		model_cluster_recommend.pickle
superstore_usa recommendation sys.ipynb		superstore_usa recommendation sys.ipynb