What is machine learning? What is it used for?
Machine learning allows computers to perform jobs that were previously solely performed by humans. Machine learning is fueling an increase in artificial intelligence capabilities, from driving automobiles to interpreting speech, by assisting software in making sense of the chaotic and unpredictable real world.
In this article, let’s explore more about what is machine learning, why is it so successful, and what are its uses.
Table of Contents
What is Machine Learning?
Machine learning, at its most basic level, is the act of teaching a computer system to make correct predictions when given data. These predictions could include determining whether a piece of fruit in a photo is a banana or an apple, detecting pedestrians crossing the road in front of a self-driving car, determining whether the word book in a sentence refers to a paperback or a hotel reservation, determining whether an email is a spam, and accurately recognizing speech to generate captions for a YouTube video.
The main difference between this and regular computer software is that no human developer has written code to inform the system how to detect the difference between a banana and an apple. There are various tools that help in predicting all this data. SQL is one such tool. There are various SQL certification courses available online and offline to help you explore more about the role of SQL in machine learning.
Why is machine learning so successful?
Machine learning is not a new method, but its popularity has skyrocketed in recent years. Deep learning has achieved new marks for accuracy in fields like voice and language recognition, as well as computer vision, resulting in this comeback.
The massive amounts of pictures, sounds, video, and text accessible to train machine-learning algorithms are one element that has enabled these breakthroughs. But the arrival of massive quantities of parallel processing capacity, courtesy of current graphics processing units (GPUs), which can be grouped to build machine-learning powerhouses, has been even more significant.
These clusters may now be used to train machine-learning models by anybody with an internet connection, thanks to cloud services from companies like Amazon, Google, and Microsoft.
What is it used for?
Machine learning algorithms are now a cornerstone of the contemporary internet and are employed everywhere around us. Machine-learning techniques are used to suggest which product you should buy next on Amazon or which Netflix film you should watch.
Every Google search makes use of several machine-learning techniques, from understanding the language in your query to tailoring your results, so anglers looking for “bass” aren’t bombarded with guitar-related results. Similarly, Gmail’s spam and phishing detection algorithms rely on machine-learning-trained models to keep your inbox free of unwanted communications.
Virtual assistants like Apple’s Siri, Amazon’s Alexa, Google Assistant, and Microsoft Cortana are one of the most visible examples of machine learning’s capabilities. Each depends significantly on machine learning to provide speech recognition and natural language understanding, as well as the necessity for a large corpus to answer inquiries.
After exploring the role of machine learning in today’s life, we can confidently say this technology is here to stay and make our lives much better.
