Why Learn Python For Machine Learning?

In today’s technologically advanced digital age, the importance of machine learning is growing. It’s increased adoption in business across industries shows how effective its algorithms, techniques, and frameworks are at solving complex issues quickly. The global machine learning market was valued at around $1.58 billion in 2017 and is expected to reach $20.83 billion in 2024 with a growth rate of almost 44.06% (CAGR).

Machine learning is popular now and grew out of the field of artificial intelligence. It is gaining popularity because modern challenges are high-dimensional and with rich data resources, it is essential to build models that solve problems in this critical space. Machine learning’s advanced tools help the models to be integrated into working software. It also supports the products that are in demand by the industries. In the current global market situation, machine learning is moving beyond bookish knowledge and textbooks. It is also creating a disruption that will revolutionize the future of the digital world.

So this article is going to tell you more about machine learning, the need to learn Python for this field, and the benefits of taking machine learning online courses.

What Is Machine Learning?

Machine Learning (ML) is an application of artificial intelligence (AI). It strictly focuses on the development of computer programs that can access data, and provide the system the ability to learn and improve with experience without being programmed. The priority of machine learning is to allow computers to learn automatically without human assistance and adjust to perform the required actions.

The process of machine learning starts with observation or data, examples, direct experience, instruction to find patterns in data to make suitable decisions. Machine learning algorithms are used in a wide variety of applications, such as email filtering, facial recognition, and computer vision. The main process of machine learning is to give training data to a learning algorithm so as to generate a new set of rules based on inference from the data. It involves various techniques to intelligently handle the huge and complex amounts of information to make predictions and decisions.

Machine learning can be categorized into three basic types:

• Supervised learning- In this category, the learning algorithm is given labeled data to obtain the desired output.

• Unsupervised learning-  In this category, the data provided to the learning algorithm is unlabeled, and is asked to identify patterns in the input data.
•  Reinforcement learning- In this category, the algorithm interacts with a dynamic environment that provides feedback in terms of rewards and punishments.

Machine learning helps to analyze massive quantities of data. It delivers faster and accurate results to identify dangerous risks or profitable opportunities. Machine learning is more beneficial when it is combined with cognitive technologies that can make it more effective in processing large volumes of information.

Why is Learning Python Beneficial for Machine Learning?

Python is a widely used high-level programming language for general-purpose and straightforward programming and has become the most important programming language while working with machine learning tools. It is an open-source language that is an interpreted, object-oriented, and interactive programming language. It also combines power with very clear syntax. It has high-level dynamic data types, classes, modules, exceptions, and dynamic typing tools.

There is an interface connection to many system calls and libraries and many different windowing systems. Python’s new built-in advanced modules are easily written in C or C++. It is also beneficial when used as an extension language for applications written in other languages that need an automation interface or easy-to-use scripting.

Learning Python is beneficial for the following mentioned reasons:

• A Great Library System- Python is preferred as the most advanced and popular programming language as it has a great choice of libraries, that includes a pre-written piece of code that allows users to reach some functionality or perform different actions. Some of the popular libraries are Scikit-learn, Pandas, Keras, TensorFlow, Matplotlib, NLTK, Scikit-image, PyBrain, Caffe, StatsModels, etc.

• A Low Entry Barrier- Python allows a low entry barrier to process data most conveniently and effectively. It’s easier language and simple syntax allows data scientists to comfortably work with complex systems.

• Flexibility- Python is considered a great choice for machine learning as it offers an option to choose OOPs or scripting to use. It is a very flexible language that developers can implement any change and see the results.

• Platform independence- Python is a versatile language that it can run with any platform including MacOs, Windows, Unix, Linux, and others. Python developers are using packages like PyInstaller to create their code for running on several platforms.

Besides the above-mentioned benefits, there are also many other advantages such as readability, good visualization options, and community support which makes Python crucial for machine learning.

Advantages of Machine Learning Course

Machine learning is proactive and specifically designed for “action and reaction” industries. It provides the ability to learn automatically to increase their accuracy with programming. There are several benefits of machine learning but it is required here to make use of the best practice to achieve the benefits and deliver the best learning experience.

A machine learning course will help you to take your career to the next level. It is the right tool to set the right platform for yourself. The course offers better growth and career opportunities year-by-year. It covers significant ground in several verticals such as image recognition, cybersecurity, facial recognition, etc. If you are pursuing a machine learning course, then there are increased chances to get better salaries. It offers you a specific set of abilities and skills, which will enable you to analyze a frightening amount of data, and then proceed to extract value and provide insights.

As there is a lack of skilled machine learning engineers to cater to new industry demands, the time is ripe for you to gain the right skills and make the most of the opportunities available.

“Machine learning can be incredibly powerful when used in the right ways and in the right place.” So start to learn machine learning today and become an expert in the field.