Udemy course R Programming for Data Science and Machine Learning by The Tech X Learners
R Programming for Data Science and Machine Learning is the best Udemy course on the market. With this offer they will be able to greatly improve their knowledge and become more competitive within the Development category. Therefore, if you are looking to improve your Development skills we recommend that you download R Programming for Data Science and Machine Learning udemy course.
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Course data:
- Author: The Tech X Learners
- Course rating: 4.5
- Category: Development
- Modality: Online
- Status: Available
- Idiom: English
Abouth The Tech X Learners
We’re a Startup aiming to provide learning with breakthrough technology. Oue courses have real time coding experience , practical applications, real-world data, in-depth learning. We care for our students. We’ll provide immediate answers to our student queries. Our courses include:
What the udemy R Programming for Data Science and Machine Learning course teaches?
What you’ll learn R Programming Language Data Manipulation with R Language Data Visualization with R Language Machine Learning with R Language Supervised Learning with R Language Unsupervised Learning with R Language Data Analytics with R Language
Learn R Programming Language for Data Science, Machine Learning, Data Analysis and Data Visualization with Libraries
More information about the course R Programming for Data Science and Machine Learning
R LANGUAGE R 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-source R 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 platforms It 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 today’s computing world. · Fast calculation With 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. · Compatible It 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. · Extensible The 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 capabilities R 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 computations R is designed to perform simple and complex statistical and mathematical computations. It can perform these operations on big data as well. · Large user base The open-source library of R provides a huge reason for the software’s large number of supporters. The highly active community of the software is the key to its massive growth. · Variety of data R’s 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 R R 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. F…
