In this data science project, you will predict borrowers chance of defaulting on credit loans by building a credit score prediction model.
In this loan prediction project you will build predictive models in Python using H2O.ai to predict if an applicant is able to repay the loan or not.
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.
Use the Adult Income dataset to predict whether income exceeds 50K yr based on
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 machine learning project, you will uncover the predictive value in an uncertain world by using various artificial intelligence, machine learning, advanced regression and feature transformation techniques.
This data science in python project predicts if a loan should be given to an applicant or not. We predict if the customer is eligible for loan based on several factors like credit score and past history.
PySpark Project-Get a handle on using Python with Spark through this hands-on data processing spark python tutorial.
In this data science project, we will predict the credit card fraud in the transactional dataset using some of the predictive models.