Text data requires special preparation before you can start using it for any machine learning project.In this ML project, you will learn about applying Machine Learning models to create classifiers and learn how to make sense of textual data.
Build your own image similarity application using Python to search and find images of products that are similar to any given product. You will implement the K-Nearest Neighbor algorithm to find products with maximum similarity.
This project analyzes a dataset containing ecommerce product reviews. The goal is to use machine learning models to perform sentiment analysis on product reviews and rank them based on relevance. Reviews play a key role in product recommendation systems.
In this spark project, we will continue building the data warehouse from the previous project Yelp Data Processing Using Spark And Hive Part 1 and will do further data processing to develop diverse data products.