Java Vs Python Vs R: Which programming language you SHOULD learn for AI – Learnxt

Java Vs Python Vs R: Which programming language you SHOULD learn for AI

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Java Vs Python Vs R: Which programming language you SHOULD learn for AI

For studying big data or machine learning, do you ever feel trapped in the dilemma of choosing the right programming language? Or being an industrialist has ever made you fall in the wonder state while analysing big data.
Three programming languages are quite popular when it comes to data science. They are Java, Python, and R. Here in this article; we will discuss these languages exclusively. We will dig deeper into the uses of these languages individually. Let us have a look at all these three languages one by one.
Java: Write once and apply everywhere
It is a programming language that can be classified as general-purpose, object-oriented, and concurrent. Java is a very compatible language that can run in almost every platform that enables its usage. 
Java Platform consists of its tools and extensions, and it provides developers with a full environment of frameworks, APIs and plug-ins, a runtime environment, and Java Virtual Machine. Simultaneously this simplifies Java Coding and creates a development environment for every developer to build and create scalable Java Applications and web systems. 
As it is one of the standard programming, enabling start-ups and enterprises to hire Java Developers. There is a vast community that can quickly help you with Java Development Project. 
Python: A multi-paradigm Programming Language
Python is a well-known programming language that is commonly used for general-programming. Great Guido van Rossum developed the programming language in 1991. Python creates a construct that enhances the programming of business verticals. 
It is the right language when it comes to automatic memory management as it is dynamic. This language can be challenging to learn, but you would express more with just fewer code lines when you use it. 
R: A perfect choice for Data Lovers and Statisticians 
R is a perfect choice if you are looking for the perfect programming language for data handling and statistics. This language provides them with the easiest way to express complex data analysis with statistics. 
Which Language is Feasible for machine learning?
You are authorised for a particular project so how you are going to choose the best language to kickstart working.  But we are providing a rundown of the languages mentioned above, and you can select them as per the complexity of the project. 
Java: Is it a Right Choice?
When you are building large-scale systems, then Java is the best for you. If you compare these three languages, then Java outperforms the other two languages. Python is faster than R, and Java is best for large scale systems. 
The development time of Java is very responsive and quick. But when it comes to statistical modelling then Java is not considered a premium choice. However, if you analyse hardcore Java, then it outperforms R and Python.
Python: Do you find it Interesting
If you are looking for smooth workflow integration, then Python can be your perfect choice. When you need to apply some data analysis techniques, you can easily integrate these features along with web apps. 
Machine learning is a boon for Python. With increased libraries like Py-Brain, Sci-kit-learn you can easily develop prediction engines and sophisticated models that you can easily integrate into your production environment quite comfortably. 
However, if some data handling is involved, then this may not be a perfect choice. The community is still hunting for a solution for it. But in the current scenario, they are nowhere near it. 
R Language: Suitable for Quality Reporting
If you are looking for a more detailed statistical analysis, then this suits you. The language was developed for statisticians if you require the right direction while working on IoT devices. This would be perfect for you as it helps to perform detailed visualisation tasks and analysis. 
This language enables you to develop high-quality reports using graphs, pie charts, etc. that give more elaboration of the findings. However, the language is not ideal if you are looking for high performance, large-scale data, and learn the ability. It is designed explicitly for the statisticians to get a hold of this you need to learn some basics of it. 
Programming languages and LEARNXT:
Considering the popularity of big data, SRM Group, in collaboration with LEARNXT, offers various data science courses. Under the data science umbrella, students can enrol them in MBA (Data Science) – Specialisations in Business Analytics & Machine Learning and Artificial Intelligence, – MSc (Applied Data Science), – PG Diploma (Applied Data Science), and – PG Diploma (Machine Learning and Artificial Intelligence) courses, etc.
This digital learning platform intends to equip students with principle concepts and data science applications, including programming languages, through experiential learning. Students can avail hands-on experience with real life-like academic projects and 2-3 month’s company-sponsored internships on real-time projects with these courses.
Students will learn emerging technologies like advanced Machine Learning, Artificial Intelligence, advanced Deep Learning, and Natural Language Processing and tools such as Python with Jupyter Notebooks, R using R Studio, Tableau, and Microsoft Excel.
Stay tuned to LEARNXT to know more about the best programming languages for artificial intelligence.
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