From the perspective of deep learning

Technology has advanced to such an extent that we no longer need to be stuck behind a desk, confined in an office building, given the digital age, we can now work remotely from which ever preferred location, all you need is your mobile laptop or better yet smart devices such as a tablet, smart phone or Notebook.

But have you ever wondered what goes on behind the scenes to make this possible? Let’s dive “into the deep’’ to find out about this interesting journey of the current Digital Age called Deep Learning. You have probably had of IT Help-desk support, so then how does a technician assist you with your technical issues, without seeing you or your PC physically. This where Deep learning as a sub-discipline of machine learning comes into play. It involves feeding data into the computer which is registered, allowing the computer to function just like the human brain.

Did you know, a computer has a human brain hence we say at times the ‘‘brain is a human computer”. Its Artificial neural network enables it to makes decisions independently.Deep learning describes algorithms that analyze data with a logic structure similar to how a human would draw conclusions. Note that this can happen both through supervised and unsupervised learning. To achieve this, deep learning applications use a layered structure of algorithms called an artificial neural network (ANN). The design of such an ANN is inspired by the biological neural network of the human brain, leading to a process of learning that’s far more capable than that of standard machine learning models. Deep learning uses a complex structure of algorithms modeled on the human brain. This enables the processing of unstructured data such as documents, images and text.

Over time, the computer may be able to recognize that ‘fruit’ is a type of food even if you stop labeling your data. This ‘self-reliance’ is so fundamental to machine learning that the field breaks down into subsets based on how much ongoing human help is involved. 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 clear images like these. Deep learning helps a machine to constantly cope with the surroundings and make adaptable changes.