In this project, we are going to talk about Time Series Forecasting to predict the electricity requirement for a particular house using Prophet.
In this machine learning pricing project, we implement a retail price optimization algorithm using regression trees. This is one of the first steps to building a dynamic pricing model.
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 uncover the predictive value in an uncertain world by using various artificial intelligence, machine learning, advanced regression and feature transformation techniques.
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, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.
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.
Machine Learning Project - Work with KKBOX's Music Recommendation System dataset to build the best music recommendation engine.
Data Science Project in Python- Build a machine learning algorithm that automatically suggests the right product prices.