Use my Docker image for demo purpose

Deep Learning for Computer Vision in Java

E-Commerce web application based on Django framework.

Product Recommendation Engine

A project for the subject "New uses of Computing Science" at Universitat de Barcelona

MVP for a recommendation engine based on Non-Negative Matrix Factorisation (NMF) [from scratch] #python #matrix-fatorization #product-ratings

An evaluation of SpringBoard's current product offering, along with an assessment of how SpringBoard can better serve existing customers.

Recommender system finds its application in many aspects of the online ecosystem including product recommendation, movie recommendation, books, news, video recommendation to name a few.

This is a code sample repository for online retail product recommendations using Collaborative Filtering (Memory-Based, aka History-Based). The source data used the famous Online Retail Data Set from UCI Machine Learning Repository.

Personalized recommender system for Sephora's cosmetics e-commerce platform. Using content-based filtering, with TF-IDF Vectorizer to extract product features and cosine similarity to recommend similar items based on user preferences. And collaborative filtering with SVD for identifying user patterns and recommending highly-rated products.

Output

Robust product recommendations using topological data analysis. 4-week project completed during Insight Fellows Program, AI Silicon Valley 2020 B Cohort

This is a demo repo demonstrating how to perform Market Basket Analysis (MBA) with a Retail (Grocery Store) sample.

Clothing Chain Sales Analysis to analyze the sales by various factors, customer ratings and product recommendation analysis

Using algorithms such as collaborative filtering, content-based filtering, or hybrid methods, this recommendation engine offers personalized suggestions to users, enhancing their shopping or browsing experience.

Deep Learning Computer Vision Web Api in Spring

Using the MovieLens dataset, will create a customer recommendation system from scratch using PyTorch.

The sample code repository leverages Azure Text Analytics to extract key phrases from the product description as additional product features. And perform text relationship analysis with TF-IDF vectorization and Cosine Similarity for product recommendation.