AI, ML, Deep Learning and Active Learning are all the Same yet Different

Mahum Khalid

  • Oct 14, 2019


Artificial Intelligence (AI), Machine Learning (ML), Deep Learning and Active Learning are all referred to as trees. But the fact remains that they all bear different fruits. Yes, they are the same but give poles apart results. In the techno-world, they are used interchangeably but it’s better that you understand how and at what level would they differ and which one would suit your needs best at the given point in time.

There are some common questions being asked repeatedly and we finally thought it’s time to address them.

Q1. What is AI?

Ans. Theoretically speaking, Artificial Intelligence comes from computer sciences, aiming to create intelligent machines. It replicates human intelligence with strictly defined rules that are fed to computers. The computer takes informed decisions on the basis of the information that has been stored in it.

Q2. What is ML?

Ans. Machine Learning is a subset of AI and it learns from the algorithms. It doesn’t require specific programming but will learn from the big data. This is quite similar to how a child learns new things with experience and creates his own sense of the world. Furthermore, ML requires labeled texts, images, videos and speech to learn and categorize data.

Q3. What is Deep Learning?

Ans. Deep Learning is the further sub-type of Machine Learning. As its very name, Deep Learning means in-depth, detailed learning. It allows a computer to learn how to perform classification tasks from images, texts, and even sounds. Deep learning presents you with the accuracy that sometimes surpasses Human-level expertise. It requires a large amount of labeled data to function properly. For instance, the driver-less cars, we looked up to, were developed using countless images and countless hours of video.

Q4. What is Active Learning?

Ans. Active learning belongs to the category where machine learning algorithms achieve higher accuracy, using the minimal training labels if only you allow it to pick and choose the data to learn from.

Technically speaking, AL is a semi-supervised machine learning algorithm, which is able to have questioned the user to get the desired results. It is also known as an optimal experimental design. So, in a nutshell, we can say, the type of machine learning that experiments and constantly learns from experience and human feedback.

Q5. How are they interrelated?

Ans. Let’s say this is a big joint family, where AI is the grandfather, ML is AI’s son, who further has two kids, namely, Deep Learning and Active Learning. They are all used interchangeably. However, since AI is the head of the family, its name is the most used and abused. Those who have a little knowledge in this field, might differentiate between AI and ML but will still use ML instead of Deep and Active Learning.

Q6. How can we help you?

Ans. As a digital marketing company in Chicago, we are fully capable of and passionate about helping you figure out how these similar yet different forms of technology can best suit your business. If you are confused about how to go ahead with this, let our esteem consultants guide you all the way through. And make your business a huge success.








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