The hardest part of learning machine learning, if you’re new to the field, is figuring out where to start. It is natural to wonder which language is best for machine learning. If you are looking forward to starting your journey in Machine Learning, we recommend you enroll in a Machine Learning Course online.
This blog will help you answer the question, “Which programming languages are popular for Machine Learning?”
- What is Machine Learning?
- Why Machine Learning?
- Popular Languages in Machine Learning
- Conclusion
What is Machine Learning?
Teaching a computer to make predictions on its own is known as machine learning. An algorithm that a computer can use to identify patterns in data and then determine what the subsequent component of the pattern should be might be created by a machine learning engineer, for instance.
Patterns can be found in many different contexts and have many different purposes.
Among the most well-known examples of machine learning is:
Machine learning is central to the operations of many of the leading companies of today, including Facebook, Google, and Uber.
A Chatbot
The most popular software application across all sectors, including banking, healthcare, education, and others, is a chatbot. Chatbots are used in all banking applications to provide customers with quick online support. These chatbots utilize machine learning principles as well.
Why Machine Learning?
Machine learning is significant because it helps companies develop new products by providing insights into consumer behavior trends and operational business patterns. Machine learning is central to the operations of many of the leading companies of today, including Facebook, Google, and Uber.
All businesses depend on data to function. Making decisions based on data-driven insights can mean the difference between staying competitive or falling further behind. Unlocking the value of corporate and customer data and making decisions that keep a business ahead of the competition may be possible with the help of machine learning.
Popular Languages in Machine Learning
Which particular language is best for a career in machine learning is a topic of much discussion.
Python
Python is a dynamic, high-level, interactive, multi-paradigm, scripting, object-oriented, high-level, procedural language that is available as open-source software. It is simple to write, the language is readable and understandable, and the English syntax is simple to read.
Python is scalable, interpretable, and flexible. It comes with a variety of built-in modules, libraries, and packages. It can run on any operating system, including Windows, Linux, UNIX, and Macintosh, making it portable.
Scala Scalable Language (Scala)
Programming languages that support multiple paradigms include Scala Scalable Language (Scala). It is a high-level language with elements of both object-oriented and functional programming. Each value is an object, just like Python, which is an object-oriented language.
Scala is a statically typed programming language that aids in the prevention of bugs in complex applications. It was initially developed for the Java Virtual Machine (JVM), and the JVM executes its source code after compiling it into bytecode.
Go (Golang)
Due to its distinctive qualities, such as its open-source status, Google ownership, and light execution, Go (Golang) has become a well-known programming language. With several tasks being completed simultaneously, it has the ability to more easily incorporate big data sets. Its positive aspect is its concurrency. It is a programming language for systems and comes with a built-in vocabulary.
It is one of the languages that is GitHub’s fastest-growing, and cloud computing services generally accept it well. It is well-liked in the infrastructure for serverless computing due to similarities to C and features like garbage collection, dynamic typing, etc.
Java
Java is renowned for backend systems and large enterprise development. It provides settings for carrying out different machine learning tasks with graphical user interfaces. The Java Virtual Machine (JVM) enables developers to create code that is identical on all supported platforms. Java applications can be created quickly and are scalable.
Julia
An open-source, high-level, versatile dynamic programming language is called Julia. Developers prefer it because of its simple syntax and the fact that it is both functional and object-oriented. It is approachable and simple to comprehend.
For high-performance numerical analysis and computational statistics, this scripting language is helpful. Its extensive mathematical function library, which provides fundamental math and scientific queries, makes it suitable for machine learning. It can be quickly deployed at large clusters, is incredibly scalable, and works best for deep learning. On all of the well-known clouds, both TPU and GPU are supported.
C++
Despite being a relatively uncommon programming language for machine learning C++ has a number of benefits. C++ is effective, provides a level of control – it enables the management of memory and single resources like the CPU – and can manipulate algorithms. It also has a number of libraries, including:
Tensorflow is an open-source library developed by Google that includes tools for computational graphs, data flow graphs, library management, debugging, scalability, and pipelining. Numerous numerical computations can be useful.
Conclusion
Python is recommended by our survey respondents if machine learning is your first foray into programming because of its wealth of libraries and simplicity of use. However, you should be ready to use Java if you want to work in an enterprise setting. Whatever the case, machine learning is in an exciting phase right now, and the journey ahead will be mind-boggling no matter what language is used. Have a fun and safe trip!
