Programming language for Machine Learning!
Machine Learning is a subfield of artificial intelligence that focuses on computing algorithms and data into the system to make decisions without being programmed explicitly. If you are new to the field of Machine Learning, there is no pain in struggling to decide where to begin. Whether you are learning new Machine Learning skills or making a career transition into the data science field, the first thing which clicks in your mind is to choose the best programming language for Machine Learning.
With more than 750+ programming languages in the market today, selecting the best programming language for your purpose is a challenging task, given each language has its pros and cons.
First, let us put things together and understand what exactly is Machine Learning technology and how many programming skills are required for a person to master Machine Learning skills:
* Machine Learning is a skill that provides the computer system with the power to automatically learn and make assumptions based upon the dataset given to the system. It can be any task: predicting whether an image has a boy or a girl, identifying if the email is spam or not, detecting credit card fraud transactions, sales of any product, and many more.
* In Machine Learning, the programmer does not write the code that instructs the Machine Learning systems to make predictions; instead, the programmers have to develop a model by writing a code in any programming language. These models learn how to make decisions and the decision-making process.
* The Machine Learning model is trained on large chunks of labelled or un labelled datasets. The end goal of the Machine Learning models is to perform actions accordingly by letting the systems learn automatically without human interventions.
How much of programming knowledge is required to learn Machine Learning?
Many factors will decide the amount of programming knowledge you need; it also depends on how he plans to use Machine Learning. But a little bit of programming background is required if one is planning to implement Machine Learning algorithms to tackle real-world problems.
Machine Learning is not all about programming; it is about understanding the fundamentals of programming, algorithms, maths, data structures, memory management, statistics knowledge, and logic is required to implement Machine Learning models.
There are many graphical and scripting Machine Learning environments like Weka, Orange, BigML, Anaconda, and others that will allow you to implement Machine Learning algorithms and methods; even if you are not a pro at programming, your fundamentals of programming are on point.
Trending Programming language
The first important task in starting with Machine Learning technology is to get familiar with the most commonly used programming languages out there.
There are many programming languages available today for us and choosing the correct language could be a confusing task. Different languages are available for other problems, and for some Machine Learning enthusiast, some languages are most commonly used by all Machine Learning Scientists worldwide.
Let us see some of the most commonly used programming languages for Machine Learning:
It remains one of the most popular languages in 2019 for popularity and usability because Python is easy to learn, open-source, faster, and gives Data Scientists flexibility and multiple ways to approach numerous problem statements. Python comes with a variety of libraries and tools that data scientists can use for various problems. Python has a vast community base and is more readable, and uses lesser code to perform the same task.
R is yet another most commonly used programming language for Machine Learning. R comes with various statistics and graphical techniques like clustering, classical statistical tests, time-series analysis, classification, linear and non-linear modelling, etc. The R programming language was designed explicitly for Data Science needs. R provides exemplary support for data wrangling, data visualization, and Machine Learning, making it the second most popular language in the Data Science field.
The third most commonly used programming language is Java because of its fast execution speed and scalability, making it a great choice when you’re thinking of building more extensive and more complex ML/AI applications. Java also comes with a great set of tools and libraries like Java-ML, MLlib, Deeplearning4j, weka, etc., which comes in handy while solving most of your ML problem statements. Java Virtual Machine makes the java code platform-independent, allowing developers to create custom tools quickly, and java has Scala, which most often comes in handy while dealing with heavy Machine Learning.
What is the best programming language for Machine Learning in 2021?
When it comes to solving Machine Learning projects and real-world problems, all three, i.e., Python, R, and Java, have their pros and cons. Still, Python is a simple, consistent, flexible, platform-independent programming language, comes with a broad community, and wins in performing some tasks such as data manipulation and some repetitive tasks. Python comes with many easy-to-use pre-existing libraries like Pandas, SciPy, sea born, matplotlib, and nltk. Hence, it would be the best programming language for Machine Learning in 2021 due to many factors that add to the language's overall popularity.