Finding the best programming language for machine learning and artificial intelligence? We’ve listed the 7 best programming languages for machine learning and AI, that you can learn in 2021.
We know that you have a keen interest in machine learning or artificial intelligence. But, you don’t know where to start right? Don’t worry we’ve listed the 7 best programming languages for ML and AI.
ML and AI are steadily gaining popularity and the demand keeps growing. The opportunity to land a job in ML or AI is a dream come true for anyone, because of their huge salary.
Machine learning and is the subset of artificial intelligence and not new a concept. The field of ML is experiencing steady growth in recent years due to the possibility of using big data.
Artificial intelligence has become a hot topic. We’ve all heard about AI’s capability from world technology leaders like Elon Musk, Sundar Pichai, Mark Zukerberg, etc.
By using AI, we can make computers think as humans do. All major social networking platforms use the power of AI to generate recommendations based on which post we’ve liked before.
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7 Best Programming Language for Machine Learning and Artificial Intelligence
Since you’re interested in learning ML and AI, you want to know which language is best suited. You should learn one of the programming languages before learning machine learning or AI.
We’ve listed the best programming languages for machine learning and artificial intelligence.
- Python
- R Program
- Java
- JavaScript
- SCALA
- Lisp
- Prolog
1. Python
Python is the best programming language for both machine learning and AI. One cannot go wrong by learning Python as it supports several fields in IT.
Python is the leading programming language where 57% of data scientists and machine learning developers use it. And it is the 33% preferred language over other programming languages.
Python supports functional, object-oriented, and procedure-oriented styles of programming.
The syntax in Python is simple to learn and easy to remember. Hence, if you are a beginner to a programming language we recommend that you learn Python. Here, you can find the list of best courses to learn Python online in Coursera and the best Python tutorial on edX.
Using Python one can put in place many algorithms in Artificial Intelligence. Python supports several libraries to make the tasks effortless.
Some of the popular libraries of Python for machine learning and artificial intelligence:
- Keras
- Scikit-learn
- Teano, etc.
Also read why you should learn Python in 2021.
2. R Program
When it comes to machine learning, R is the second most preferred language after Python. If you’ve prior programming experience in another language, then you can understand R.
It is a graphic-based programming language that is used for data analysis, statistical computing, and visualization in ML.
Among statistic enthusiasts, R is the popular programming language. R is also used in machine learnings tasks such as classification, regression, and decision tree.
R programming language is generally used in data science.
Very often Python and R are compared and misunderstood. But they both are completely different languages used for different purposes.
Some of the popular packages of R are:
- Gmodels
- Class
- Tm
- RODBC
The above packages make it effortless to execute in machine learning algorithms.
3. Java
The third most preferred programming language for ML and AI is Java. Java is a secure language because of its bytecode and sandboxes.
The many benefits of the Java language include ease to use, package services, ease of debugging, and better graphical representation of data.
You might not know that along with the latest and old machine learning algorithms are written in Java.
Java’s support for functional programming language style allows future ML systems with speed, accuracy, and precision.
The latest version of Java has improved many of its features for machine learning such as:
- New file methods – readString, writeString, and isSameFile.
- New string methods – strip, stripLeading, stripTailing, isBlank, lines, and repeat.
- Pattern recognizing methods – asMatchPredicate.
If you’re looking for a job in an enterprise environment, then you should prefer to learn Java.
4. JavaScript
The most generally used programming language for web development is JavaScript. Many new data scientists and machine learning developers prefer to use JavaScript. Because it helps to visualize the results of ML algorithms.
Using JavaScript along with Node.js makes it the most popular programming language. JavaScript is both an interpreted and dynamically typed language.
If your interest is in web development then you should concentrate on JavaScript. Because JavaScript is limited to only web development. You can build powerful web applications by leveraging ML and AI.
5. Scala
Scala is the core language that is supported by the Apache Spark platform. It is a data platform that offers functionalities for machine learning and big data processing through its MLLIB library.
Scala offers programmers to develop, code, design, and deploy ML algorithms provided by Apache Spark or other big data technologies.
Scala programming language has many well-developed libraries that are used in:
- Linear algebra
- Random number generation
- Scientific computing
6 Lisp
Of all the programming languages that are mentioned in this list, Lisp has the longest history. It is a family of programming languages with popular dialects that are Common Lisp and Clojure.
Because of its longest history, it had a huge influence on the development of Python, R, and JavaScript.
Lisp is the most difficult programming language, hence it is not recommended for beginners.
Lisp can be used to create Chatbots for e-commerce websites. The modern application that uses Lisp is Grammarly.
7. Prolog
Prolog language stays alongside Lisp when it comes to development in AI. Some of the popular features of Prolog are:
- Pattern matching
- Tree-based data structuring
- Automatic backtracking
The above features make the Prolog language be powerful and flexible programming framework. It is generally used in medical projects and for designing advanced AI systems.
Resources to Learn the Programming Language
We’ve listed the two best resources to learn the programming language. You can either learn from Edureka or DataCamp. Both of them offer competitive learning but a different approach.
Edureka offers instructor-led training whereas DataCamp offers self-paced training.
Although both offer a good training platform, make sure which study method aligns best. Our personal favorite is DataCamp because they have a subscription model which offers all their course for a monthly or annual membership.
If you’re new to programming we recommend you to read the 5 easiest programming languages to learn first.
Summary
If you’re experienced in any other programming language then learn R as it is easy to understand. Learn Python if you’re new in programming and never had any experience in programming.
Consider learning JavaScript if your interest lies in the boundaries of web development. If you have a programming experience that is already mentioned in the list then you are good to go ahead to learn ML or AI.
Avoid learning Lisp as it is very hard to learn and master. Please share this article with your friends and colleagues if they are interested in learning one of the programming languages.
If you’re looking for the best online resources to learn Machine Learning then you should check out this list here.
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