In this project, we are going to work on Deep Learning using H2O to predict Census income.
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.
Machine Learning Project in R- Predict the customer churn of telecom sector and find out the key drivers that lead to churn. Learn how the logistic regression model using R can be used to identify the customer churn in telecom dataset.
Machine Learning Project in R-Detect fraudulent click traffic for mobile app ads using R data science programming language.
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.
Data Science Project in Python- Build a machine learning algorithm that automatically suggests the right product prices.
In this data science project, we will predict the credit card fraud in the transactional dataset using some of the predictive models.
In this project, we are going to talk about H2O and functionality in terms of building Machine Learning models.
In this data science project in R, we are going to talk about subjective segmentation which is a clustering technique to find out product bundles in sales data.
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.