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Estimating churners before they discontinue using a product or service is extremely important. In this ML project, you will develop a churn prediction model in telecom to predict customers who are most likely subject to churn.
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.
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.
In this time series project, you will build a model to predict the stock prices and identify the best time series forecasting model that gives reliable and authentic results for decision making.
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 census data.
Data Science Project in R-Predict the sales for each department using historical markdown data from the Walmart dataset containing data of 45 Walmart stores.
In this data science project, you will work with German credit dataset using classification techniques like Decision Tree, Neural Networks etc to classify loan applications using R.
In this R data science project, we will explore wine dataset to assess red wine quality. The objective of this data science project is to explore which chemical properties will influence the quality of red wines.
Data Science Project - Build a recommendation engine which will predict the products to be purchased by an Instacart consumer again.
Machine Learning Project in R-Detect fraudulent click traffic for mobile app ads using R data science programming language.
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 Deep Learning Project, you will use the credit card fraud detection dataset to apply Anomaly Detection with Autoencoders to detect fraud.
In this data science project, you will learn to predict churn on a built-in dataset using Ensemble Methods in R.
Learn to classify the sentiment of sentences from the Rotten Tomatoes dataset. You will be asked to label phrases on a scale of five values: negative, somewhat negative, neutral, somewhat positive, positive.
In this machine learning project, we will use hundreds of anonymized features to predict if customers are satisfied or dissatisfied for one of the biggest banks - Santander
In this machine learning project, you will build predictive models to identify wine preferences of people using physiochemical properties of wines and help restaurants recommend the right quality of wine to a customer.
Machine Learning Project in R -Predict which customers will leave an insurance company in the next 12 months.
In this machine learning project, we will predict which coupons a customer will buy.
In this project, we will try to predict how often players playing a video game called PUBG will win when they play by themselves.
Given a partial trajectory of a taxi, you will be asked to predict its final destination using the taxi trajectory dataset.
The two programming languages that Data Scientists widely use for Data Science projects are R and Python. Often beginners in Data Science try to compare the two languages and prepare their own checklist of Python Vs. R. If after preparing that checklist, you are still confused and want to know for what kind of Data Science Projects, R is a better choice, then check out the R projects from ProjectPro repository that Industry experts have prepared. Through these R programming projects with source code, you’ll understand how Data Science experts implement various machine learning algorithms for solving data science problems.
Based on your experience with R programming projects, you can choose from any of the following categories that list different R programming projects with source code.
To make the most out of data science projects, one critical factor in choosing a project in R that is at the right skill level – neither too hard nor too easy. If you are a data science beginner, selecting a data science mini-project in R at an appropriate skill level will minimise your skills gap and help you learn new data science skills on the fly on the completion of the project. Below are our industry experts recommendations on some of the must-do projects in R for Data Science Beginners –
If you fancy sipping wine, you will enjoy working on this R language product. The aim of this project is to guide you through the task of using machine learning models for identifying the wine preferences of people. The physicochemical properties of wines will be used as features to help restaurants suggest the correct quality of wine to a customer.
This project is a very common project on R programming that you will find in the bucket list of a beginner in Data Science.