Machine Learning Coding: What Do You Need to Know?

These days, machine learning is booming, and it’s difficult to find a situation where it isn’t applicable. Machine learning is attracting workers from a variety of fields, many of whom are drawn to the field’s math and statistics. However, the programming required to put machine learning models into practice is their biggest roadblock. We will talk about the requirements for machine learning in this article when it comes to the coding portion. We’ll examine the level of coding proficiency needed if one is interested in working in a  Machine learning field.¹ 

What is Machine Learning?

“Machine learning is an application of Artificial Intelligence. It learns from the provided data by finding patterns in it, allowing any new data to be automatically classified, with minimal or no human intervention. Machine learning uses a large amount of data to train and predict new values.”¹ 

Machine learning is prevalent and used in almost every aspect of life, including:

• Automatic vehicles
• Recognition of speech
• Identification of fraud
• Suggestions for products
• Detection of malware threats¹ 

Types of Machine Learning

Machine learning is usually divided into three categories  that include:

• Supervised Learning: To train the machine, it is exposed to massive amounts of labeled data, such as photos of numbers, which allows them to distinguish between numbers and recognize clusters.
• Unsupervised Learning: Based on the similarity between data, algorithms will help identify patterns in data and categorize them into clusters.
• Reinforcement Learning: The process of teaching models to choose actions that will maximize output in specific scenarios.After the model has been trained with input, the user will decide whether to reward or penalize it based on its output.¹ 

Does Machine Learning Require Coding?

Coding enables the training, testing, and evaluation of machine learning models as well as their implementation on computer systems, so the answer is that it is an essential component of machine learning. Coding is required for the ML algorithms because it is the only way to interact with computers and direct them to perform specific tasks.¹ 

Since code is used to implement machine learning algorithms, it is beneficial to have a solid foundation in coding. It is advisable to learn at least one programming language because it will significantly improve your understanding of the inner workings of machine learning. While you can get away with being a novice programmer and concentrating on the math front, it is still advised. But you need to learn a programming language that makes using machine learning algorithms simple.² 

A few well-liked programming languages are listed below:

1. Python is a popular language for machine learning, especially among beginners, due to its simple syntax, built-in functions, and extensive package support. Most libraries are supported by it. Over 235,000 packages are available through the Python Package Index. Additionally, the Python learning community is very supportive. With Python, you can use NumPy for mathematical operations, TensorFlow for deep learning, OpenCV and Dlib for computer vision, scikit-learn for algorithms for classification and regression, pandas for file operations, etc.¹ 

2. R is another requirement for Artificial Intelligence(AI) and machine learning that is as popular as Python. R is now used to implement many machine learning applications. Graphs and good library support are included. Some of the important packages that R supports are Kernlab and Caret for regression and classification-based operations; DataExplorer for data exploration; Mlr3 for machine learning workflows; Plotly and ggplot for data visualization; etc.² 

3. Java is gaining popularity among machine learning engineers from Java backgrounds, despite Python and R still being the favorite languages of machine learning enthusiasts, because they don’t need to learn a new programming language like Python or R to implement machine learning. The majority of the open-source tools for big data processing, like Hadoop and Spark, are written in Java, and many organizations already have sizable Java codebases. It is simpler for machine learning engineers to integrate existing code repositories with Java for machine learning projects. It’s simplicity of use, package services, improved user interaction, simplicity of debugging, and graphical data representation make it a preferred machine learning language.³

Along with being familiar with the essential machine learning prerequisites, you should also be skilled at working with data. This skill is essential if you intend to take machine learning seriously. Here, we covered some of the most important requirements for machine learning, including some well-liked programming languages that it relies on. Thus, machine learning requires knowledge of coding.

To learn more about programming languages and other coding related topics, visit BYJU’S FutureSchool Blog.

References:

1. Is Coding Required For Machine Learning. (n.d.). Retrieved July 14, 2022, from https://www.analyticsfordecisions.com/is-coding-required-for-machine-learning/ 
2. Best language for Machine Learning: Which Should You Learn? (n.d.). Retrieved July 14, 2022, from https://www.springboard.com/blog/data-science/best-language-for-machine-learning/ 
3. Top 5 Programming Languages and their Libraries for Machine Learning in 2020 – GeeksforGeeks. (n.d.). Retrieved July 14, 2022, from https://www.geeksforgeeks.org/top-5-programming-languages-and-their-libraries-for-machine-learning-in-2020/