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Top Programming Languages of 2019

With rise in technologies like AI and Machine Learning, we saw various applications of programming languages this past year, each with it's unique advantages. Although we didn't see many new languages last year, Julia, a comparatively new programming language saw some popularity among the ML groups. Given below may be a list of the highest languages utilized in 2019.

Top Programming Languages for AI & Machine Learning in 2019:

Python:

Python is one among the highest programming languages thanks to its simplicity. The syntax and arrangement of Python is straightforward to find out . Object-oriented programming, functional programming also as procedure-oriented sort of programming are supported by Python. variety of libraries exist within this programming language , making our tasks simpler. NumPy is one among them. NumPy helps us settle numerous logical calculations. Python offers rapid prototyping compared to other programming languages like Java or C++. It are often utilized in numerous AIML courses and requires a smaller number of code lines compared to other programming languages.

R:

R may be a full-fledged software that's used for statistical computing and visualization, it's a free and open-source programming language , allowing it to be easily accessed. Programmers can learn from the ASCII text file and modify it as needed . R has been in use for an extended time now and has been utilized in areas like bio-engineering and bioinformatics. it's one among the simplest programming languages when it involves statistical purposes because it is beneficial for controlling and analyzing data. it's various packages like RODBC, GModels, and these are utilized in the sector of AI and ML. These packages allow the language to implement ML Algorithms easily. R also features a wide utilization within the banking sector.

Java:

The existence of Java dates back way before Python, and it works well for Machine Learning development. It provides many benefits like , simple use, package services, simplified work with large-scale projects, graphical representation of knowledge and better user interaction. Game development and mobile application development also can be done using Java. one among the foremost popular toolkit for Java is Weka, this contains tools for data pre-processing, classification, regression and visualization. Another library called Deeplearning4j which is specially designed for Java, provides support for deep learning algorithms.

Julia:

Compared to the opposite programming languages, Julia may be a newer, high-level, free programming language . it's rapidly being adopted by the tech also because the finance community thanks to its ability to execute ML Algorithms at a quick speed. Investment banks are using Julia for time-series analytics and insurance companies are using it for risk calculation. one among the main advantages is that Julia is provided with Flux. Flux provides a versatile interface which will be modified to make advanced models. a number of the tools available for Julia are a linter, profiler, debugger package and lots of more. Julia is adaptable to existing ML frameworks like TensorFlow and MXNet.

C/C++:

C++ may be a general-purpose language developed as an extension for the favored C programming language . it had been planned with an inclination towards resource-constrained software and enormous systems, effectiveness and adaptableness of utilization as its main features. most of the people start with C/C++ as their first programming language . C/C++ is employed within the area of AI in Gaming. it's sophisticated libraries like Mlpack, which may be a fast and versatile ML Library. the most aim is to implement ML Algorithms at a faster speed.

What does one think 2020 has future for us? Will we see newer, faster and efficient languages or, will the prevailing ones become the scripts of all future algorithms.

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