In this project, we are going to talk about H2O and functionality in terms of building Machine Learning models.
Data Science Project in Python- Build a machine learning algorithm that automatically suggests the right product prices.
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.
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.
In this project, we are going to work on Sequence to Sequence Prediction using IMDB Movie Review Dataset using Keras in Python.
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.
The goal of this data science project is to build a predictive model and find out the sales of each product at a given Big Mart store.
Machine Learning Project - Work with KKBOX's Music Recommendation System dataset to build the best music recommendation engine.
In this data science project, we will predict the credit card fraud in the transactional dataset using some of the predictive models.