R Programming for Data Science and Machine Learning | Data Science Online Course by Udemy

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R Programming for Data Science and Machine Learning

R LANGUAGER language is an open-source programming language that is used for statistical analysis and graphical representation. It was developed by Ross Ihaka and Robert Gentleman, at the University of Auckland, New Zealand. R contains a large and coherent system of statistical and graphical techniques that can be used for data analysis. It provides a well-defined environment for reproducible research.R is an implementation of S programming language, inspired by Scheme. A lot of data scientists, statisticians, analysts etc. use R to make sense of the data and then use it for data analysis, predictive analysis and data visualization. The data analysis can be done by writing scripts and functions in R language. It is an object-oriented language that provides modeling, exploring and visualizing of the data. The process of data analysis is usually done in a few lines of code. R provides all the functions regarding data manipulation, statistical model or chart that an analyst could need. It includes machine learning algorithms, linear aggression, time series, statistical interference etc. R is written in its own language which makes programmers to understand the format easily, but for heavy computations it collaborates with C, C++, Python, etc. Features Open-sourceR language provides an open-source, free of cost platform. It is licensed by GNU, General Public License, this means that anyone can download it and make changes in it according to the prerequisites. Many other packages are available under the same license and can be downloaded easily. Runs on all platformsIt supports cross-platform operations, this means that the software operates correctly on all other platforms i.e. Windows, Linux and Mac. Technology that functions on all platforms has multiple benefits to reap in todays computing world. Fast calculationWith the help of R, you can carry a vast variety of complex operations on vectors, arrays, and other objects. These objects perform rapidly which allows the programmers to carry out these calculations easily. CompatibleIt is highly compatible with other programming languages. It can use C or C++ for complex tasks. Java and Python can also be used for heavy tasks. Other than that, R is compatible with other data processing technologies as well. It can be easily paired with Hadoop or Spark to process large data. ExtensibleThe extensible feature of R makes it capable of being used in a variety of fields. It is used by lots of data scientists and data miners for feasibility. R is widely used in Machine Learning, Data Science and Artificial Intelligence for better data processing and analyzing. Graphical capabilitiesR is capable of producing static graphics with good quality visualization and had libraries that provides graphical capabilities. This makes data visualization and representation quite handy. Complex statistical computationsR is designed to perform simple and complex statistical and mathematical computations. It can perform these operations on big data as well. Large user baseThe open-source library of R provides a huge reason for the softwares large number of supporters. The highly active community of the software is the key to its massive growth. Variety of dataRs remarkable storage and data handling techniques allows it to handle a variety of structured and unstructured data. It also provides data operation and data modeling facilities due to the interaction with storage facility. Application of RR has played a huge role in shaping the industries. As artificial intelligence and machine learning are the backbone of the businesses nowadays, R is a basic component of artificial intelligence and machine learning. The companies opt for R because it is easy to learn. If you want the best insights from the data, it is necessary to spend time in learning the appropriate language for accurate outputs and R provides all the essential tools and techniques that are required. Following are some of the major applications of R:1. Fundamental tool for financeR is one of the most used languages in finance. The statistical computation reaps many benefits to the data scientists in the field. R provides the facilities of data mining that is extremely useful. It is also widely used for credit risk analysis. The statistical processes provided by the software are used to determine the movement of stock market and predict the future prices of shares.2. Data scienceR is a popular language in the field of data science. The valuable techniques of statistical computations and graphics prove to be extremely beneficial for data scientists. It is widely used by data statisticians and data miners all over the world.3. Data importing and cleaningThe software is commonly used by the quantitative analysts and helps in data importing and cleaning.4. HealthcareR is extensively used in the healthcare industry for data analysis and processing. It is used to design clinical trials, compare therapies, evaluate drugs by running PD analysis, run data validation against errors and frauds, transform data

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