In this project, we are going to talk about H2O and functionality in terms of building Machine Learning models.
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.
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.
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.
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.
In this machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.
Data Science Project - Build a recommendation engine which will predict the products to be purchased by an Instacart consumer again.
There are different time series forecasting methods to forecast stock price, demand etc. In this machine learning project, you will learn to determine which forecasting method to be used when and how to apply with time series forecasting example.
In this project, we are going to talk about Time Series Forecasting to predict the electricity requirement for a particular house using Prophet.
Data Science Project in Python- Build a machine learning algorithm that automatically suggests the right product prices.