Is Deep Learning Better Than Machine Learning?

Overview :

What is deep learning?

When, where and why is deep learning used.

Is deep learning better than conventional machine learning?

Which came first? The chicken or the egg?

Centuries have passed and still we haven’t been able to answer this question. But soon, maybe a machine will! Can it? Will it? Let’s figure out!

Introduction :

What is deep learning? How is it related to machine learning? Is it better than conventional machine learning? A lot of questions at once, isn’t it? Deep learning is a part of the machine learning family which is based on the concept of evolutionary algorithms. It basically mimics biological processes like evolution.

So what exactly is machine learning?

Machine learning is a subset of AI that uses statistical strategies to make a machine learn without being programmed explicitly using the existing set of data. It evolved from the study of pattern recognition in AI. For a detailed understanding of machine learning, you can watch this video-

Machine learning and deep learning can be daunting and difficult to learn by yourself. A gamut of online free courses have come forward to make things simpler but if you want to take up a rigorous well-respected course that employers will respect then the Machine Learning Online Certification program by GreatLearning  which offers 130 hours of content and personalised mentorship in an extremely easy to grasp manner is an excellent choice.

Deep Learning:

Conventional machine learning methods tend to succumb to environmental changes whereas deep learning adapts to these changes by a constant feedback and improve model. Deep learning is facilitated by neural networks which mimic the neurons in the human brain. Deep learning embeds multiple layer architecture (few visible and few hidden). So, deep learning is an advanced form of machine learning which collects data, learns from it and optimises. Often some problems are so complex, it is practically impossible for the human brain to comprehend it so programming it is a far fetched thought. Primitive forms of apple’s siri and google assistant are an apt example of programmed machine learning as they are found effective in their programmed spectrum. Whereas, Google’s deep mind is a great example of deep learning. Essentially, deep learning means a machine which learns by itself by multiple trial and error methods. Often a few hundred million times!

A simple understanding of basic deep learning concepts can be grasped from this video on neural networks:

Now that was pretty impressive, right?

Let us think of writing a program which differentiates between an apple and an orange. Although it may sound like a simple task to accomplish, it is indeed a complex one as we cannot program a machine to know the difference merely by observing it. We as humans can, machines can’t! So if we were to program, we would mention a few specifications of the apple and the orange but it would work for simple and cleare images like these.

But what if we place a banana?

The machine would probably be befuddled! This is where deep learning comes into the picture. A conventional machine learning method helps a machine to efficiently perform only a predetermined set of instructions and tends to become unworthy in case new variables are introduced in the system. It can be understood better with this video: 





So, how do machine learning and deep learning differ from each other? This article covers it in detail:

Deep learning helps a machine to constantly cope with the surroundings and make adaptable changes. This ensures versatility of operation. To elaborate, deep learning enables a machine to efficiently analyse problems through its hidden layer architecture which are otherwise far more complex to be programmed manually. So, deep learning gets an upper hand when handling colossal volumes of unstructured data as it does not require any labels to handle the data.

So Let’s Summarize :

Deep learning is an advanced form of machine learning which comes in handy when the data to be dealt with is unstructured and colossal. Thus, deep learning can cater to larger cap of problems with greater ease and efficiency. Technological breakthroughs like Google’s Deepmind is the epitome of the heights that current AI can reach facilitated by deep learning and neurological networks.

So maybe we can’t predict which came first, the chicken or the egg but will AI be able to? Stick around to find out!

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