R is a popular beginner-level programming language. It is a free software first developed by Robert Gentleman and Ross Ihaka in 1993. R has a detailed catalog of graphical strategies and applied mathematics that additionally makes good use of simple and linear regression, machine learning algorithms, applied mathematics, and statistics. Most R libraries are programmed in R, except for more complex machine tasks and algebraic language codes.
As a budding programmer, you must work on various projects to gain a good knowledge base regarding how programming languages are put to industrial use. Working on data science projects is bound to increase your knowledge and the ability to showcase your data analysis skills. You can hone your coding skills and work with large datasets by working on real-time Data Science projects.
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This article will discuss the best R projects topics to help you build a strong base in Data Science.
The Best R Project Ideas
Here is a compiled list of the ten best R project ideas for budding programmers to get a hands-on experience:-
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Detection of Credit Card Fraud
With the increasing number of credit card frauds, you can easily create an application to detect a fraudulent transaction made with a credit card via R programming. Different Machine Learning algorithms can be designed to identify the difference between a genuine transaction and a fraudulent transaction. In this project, you must use algorithms such as Regressions, Decision Trees, Artificial Neural Networks, and the like.
The fraud detection system uses the dataset named “card transaction”. It comprises both authentic and fraudulent transactions. For this project, you must follow steps like exploring data, importing the transaction dataset, structuring, manipulating, modeling, fitting, and implementing algorithms.
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Sentiment Analysis
With sentiment analysis, you will analyze words to discover sentiments and opinions with different polarities ranging from positive, negative, and neutral. The method is also often called opinion mining and polarity detection. In this classification type, data that comprises the said sentiments is divided into various classes that can be neutral, binary, i.e., either positive or negative, or even multiple emotions like sad, happy, angry, etc.
This process of analyzing sentiments is mainly used to determine the kind of opinions reflected in websites, documents, social media feeds, and more. You can build this relatively easy project using R programming and datasets from the “janeaustenr” package.
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Analysis of Uber Data
Data storytelling is one of the main components of Machine Learning used by many companies to decipher the context and background of numerous operations. On the other hand, data visualization also helps companies understand complicated datasets that influence decision-making.
One of the best projects in data visualization is the Uber Analysis Project. In this project, R programming and libraries are essential for analyzing variables and parameters like the day trips, monthly trips, and annual trips. The visualizations for various yearly time-frames are built with the help of ‘Uber Pickups in New York City Dataset.’ You will need to import R packages and libraries including “ggthemes”, –“ggplot2”, ”dplyr”, ”lubridate”, “DT”, “tidyr” and “scales”.
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Wine Quality Prediction
With the help of predictive modeling, the idea of improving wine quality can be efficiently executed. In this project, you will need to access the “red wine” dataset to determine the quality of the wine. This project’s primary aim is to explore red wine’s chemical properties.
For starters, you must use the input variables to predict the wine quality and classify the wines with exceptional attributes. Then, you must determine the unique relationship within the data via the dataset and brush up on the plots to highlight it. You will learn more about data exploration, data visualization, and regression models in this project.
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Music Recommendation System
You can easily set up an auto-play music system using the R language. This is a project where you will learn to use the engine for music recommendation to determine one’s music interest and make songs play accordingly.
This project is similar to a system that aids in movie recommendations where you need to build a system that suggests songs instead of movies and web series. This project uses the dataset from KKBOX, one of the top music streaming services with a library of millions of music tracks. Here, you will need to build a machine learning system with the help of Python and R. You can detect how often a user listens to a song after listening to it for the first time, initiating the first listening event in a particular period.
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Identification of Product Bundles
Product bundling is a foolproof marketing strategy that uses various products to sell as a single product at a discounted price. Companies use this strategy to encourage customers to buy more products from them. One good example is the meal combo from Pizza Hut and Dominos.
In this project, you must use the clustering technique and subjective segmentation to bundle products together to make good sales. You can also use datasets like the “weekly sales transaction” that consists of the purchase quantities of various products.
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Classifying Data Sets
The set of machine learning practices for constructing a set of classifiers and classifying data points by taking note of their predictions is called an ensemble algorithm. The most basic method of ensembling is called Bayesian averaging, which has been updated with newer algorithms, like bagging, boosting, and error-correcting output coding. Machine learning and ensemble methods are the new norms that make up the data variability dynamics in this AI-based digital age.
With the help of this ensemble method used for data classification and prediction, you can participate in one of the best beginner’s projects with R programming.
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Prediction of Churn for Telecom Companies with Logistic Regression
Every company’s motive is to increase profit and revenue by acquiring new customers and ensuring that the existing ones always come back. It is also essential for companies to determine beforehand if the customers want to discontinue using their services to avoid negative consequences. You must build a chur model to enable this feature. The chur model suggests the output that indicates the warning about the customers who want to discontinue or, in other words, “churn”. For this project, you must use the R programming Logistic Regression model that you need to integrate with customer datasets.
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Speech Emotion Recognition
This project, you will learn to identify human emotions via sample voices or direct speech. It is based mainly on the extraction of emotions from a recording. In this project, you will need the library Librosa, often used for analyzing audio and music. With R, additionally, you will use neural network algorithms, support vector machines, and convolution neural networks.
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Movie Recommendation System
This project is similar to the music recommendation system. The only difference is that it tracks the watching pattern of viewers and suggests movies and videos in accordance. In this project, you must use the user’s browsing history data. The greatest advantage of building this movie recommendation system from the start is that you will learn the inner workings of a recommendation engine. You must use the R language and packages like recommender lab, ggplot2, reshape2, and data.table.
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Conclusion
Working on R project ideas is an excellent way to develop a strong understanding of Data Science. In each of these projects, you must create accurate models. In the learning process, you will acquire industry-relevant skills. If you want to learn more about R project ideas and data science, you can sign up for the premium Advanced Certificate Program in Data Science available in upGrad.
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