Use the Amazon Reviews/Ratings dataset of 2 Million records to build a recommender system using memory-based collaborative filtering in Python.
In this NLP AI application, we build the core conversational engine for a chatbot. We use the popular NLTK text classification library to achieve this.
In this data science project, you will predict borrowers chance of defaulting on credit loans by building a credit score prediction model.
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.
Data Science Project in R -Build a machine learning algorithm to predict the future sale prices of homes.
In this ensemble machine learning project, we will predict what kind of claims an insurance company will get. This is implemented in python using ensemble machine learning algorithms.
In this machine learning project, we will use binary leaf images and extracted features, including shape, margin, and texture to accurately identify plant species using different benchmark classification techniques.
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.
Music Recommendation Project using Machine Learning - Use the KKBox dataset to predict the chances of a user listening to a song again after their very first noticeable listening event.
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.