Deep Learning Vs Machine Learning: Is There A Difference?

by Pranav Ramesh
April 09, 2021
Difference Between Machine Learning and Deep Learning

If what you do is in any way connected to artificial intelligence (AI), then you must have come across the terms Deep Learning and Machine Learning quite often. But unless you are an AI engineer or data scientist, you most likely have no idea what these terms mean, or how they differ from each other. The fact that people have a tendency to use them interchangeably doesn’t help either. In this article, we are going to explore what deep learning and machine learning are, as well as some related terms, and explain why they are different.

Topics covered

  • What is Machine learning?
  • What is Deep Learning?
  • How are they different?
  • Associated terms

What is Machine learning?

Machine learning (ML) is a type of artificial intelligence programming that was created in the 1950s. It focuses on building applications that can use data to learn and become more accurate over time, without additional programming. To put it another way, machine learning is the science of getting computers to process data, make assumptions and act on them, without explicitly being told what to do.

Machine learning programs are developed by machine learning engineers. It is their job to create programs and algorithms that teach machines to take action independently. Machine learning engineers are some of the most sought-after professionals in IT today—and some of the highest-paid—which should tell you something about how important machine learning is to our modern world.

To know more about machine learning engineers and other AI-related jobs, check out our other article titled 5 Popular Artificial Intelligence Jobs and the Companies that Offer Them.

Where is Machine Learning used?

One of the most popular uses of machine learning is in recommender systems, which is used extensively by Google. You must have noticed that whenever you search for something on Google, this has an impact on your recommendations on YouTube and other Google services. This happens because Google’s AI can learn from your searches and recommend content that would be suited to your interests. Amazon also uses a similar machine learning-based AI to tailor your shopping recommendations.

Machine learning is also used extensively by speech-to-text converters, computer games, image recognition software, and for medical diagnosis and predictive analytics. It is a building block of any AI-driven consumer product today.

RELATED: Difference between Artificial intelligence and Machine Learning

 

What is Deep Learning?

Deep Learning is a subset of machine learning that can be considered an advancement in the field. As IBM puts it, all deep learning is machine learning but not all machine learning is deep learning. Deep learning is about using multiple layers of analysis to extract higher levels of understanding from data.

Deep learning algorithms use what is known as an artificial neural network (ANN), that imitates the human mind, and helps computers process information the way a human brain would.

Where is Deep Learning used?

The most successful application of deep learning so far has been in large-scale automated speech recognition. Even though speech recognition software has been in development for decades, it was the advent of deep learning that helped it enter the mainstream. Alexa, Siri, Google Assistant, and pretty much every other AI assistant operate on speech recognition software developed using deep learning.

Outside of speech recognition, deep learning is also used in drug research, mobile advertising, computer gaming, robotics, and banking.

Deep Learning vs Machine Learning: How Are They Different?

When we talk about machine learning vs. deep learning, what we are really comparing is two different methods of reaching the same end goal