Coursera Learner working on a presentation with Coursera logo and
Coursera Learner working on a presentation with Coursera logo and

There has been lots of conversation regarding the various possibilities and opportunities arising from machine learning. Experts believe this technology could be incredibly helpful for homes, offices, warehouses, factories, and many other things. Technology is rapidly evolving, and terms like deep learning, machine learning, and artificial intelligence could be perplexing for some individuals.

Are you one of those people too? This guide will eliminate your confusion by talking about deep learning fundamentals. We will also discuss some practical examples to ensure you comprehend deep learning technology completely. 

Deep Learning – What is it?

Many of you reading this most likely know about artificial intelligence. The technology can enable machines to perform tasks that usually require human knowledge. It encircles machine learning as some devices can understand by experience and gather skills with little to no human involvement.

It would be fair to claim that deep learning is a machine learning subset where artificial networks (neural) and algorithms learn massive amounts of data inspired by humans. Deep learning algorithms are quite similar to human beings because they can also learn from experience. By doing so, they can perform repetitive tasks. You can make some tweaks and changes until you get your desired outcome.

Experts use the coined the term “deep learning” for a particular reason. The algorithm contains a multitude of deep layers that help with the learning procedure. Almost every problem needs to think to find a solution. Deep learning uses the same strategy and is capable of learning almost anything. Of course, it cannot do everything we can but expect this technology to become more sophisticated soon. 

You would be surprised to see the high amount of data generated every day. Several pieces of research suggest that the world makes almost three quintillion bytes each day.  It is a significant reason why deep learning is possible. Deep-learning-based algorithms require tons of data to comprehend new concepts and evolve, for those who do not know. The rapid rise of data creation is a massive reason behind the recent growth of deep learning characteristics and capabilities. 

Besides the presence of extra data, deep learning algorithms take advantage of modern computing powers due to Artificial Intelligence’s proliferation as a service. Judging A.I solely as a service has been remarkably beneficial for organizations. Why? Because businesses have easy access to this technology. Furthermore, organizations can acquire the artificial intelligence algorithms needed for deep learning without sizeable investments. 

Deep learning Artificial Intelligence enables machines to find accurate solutions to complex problems despite using inter-connected, unstructured, and diverse data sets. As discussed earlier, deep learning algorithms evolve through learning. So, it would be best to expose them to new ideas to improve the algorithm’s performance. 

Understanding Deep Learning through examples

We live in a time in which machines can solve complicated issues without human interference. You must be wondering what precisely are the problems they are resolving. Let us discuss some tasks supporter by today’s deep learning A.I. However, bear in mind that the list will become longer as algorithms will evolve with their exposure to new data.


Deep learning algorithms provide automatic translations between various languages. It is an excellent feature for government officials, business people, travelers, and anyone who travels frequently.

Virtual Assistants

Whether it’s Cortana, Siri, or Alexa, most online service providers have virtual assistants utilizing deep learning to comprehend human language and speak to respond to our commands. We would not be able to interact with these assistants without the deep learning A.I.  

Image Colorization

Transforming white and black images used to be a complex task. It required hours, and sometimes, days to complete image colorization by human hand. Things are vastly different today as deep learning algorithms can use the objects and context in images and videos to color them and recreate white and black photos and footages in color. You’d be surprised to see the accurate and impressive results. 

Facial Recognition

Numerous organizations, especially tech-giants, are using deep learning for facial recognition. It is a unique technology to simplify security as it helps recognize familiar faces in its data feed. Social media applications like Instagram, Snapchat, and Facebook use deep learning to tag people in images. Some experts predict that we could buy items from online stores by merely showing our faces in a few decades. 

However, deep learning algorithms are still facing some challenges. The A.I fails to recognize people with shaved beards, changed hairstyles, and various other differences. You can even manipulate deep learning if your images contain obstructions or bad lighting. However, these issues could vanish rapidly as this technology is becoming more sophisticated by the day. 

Personalized Entertainment and Shopping

Are you an avid Netflix user? You most likely wonder how it suggests you movies or T.V shows or how Amazon knows precisely what it should recommend you. What’s most surprising is that these recommendations often make sense. These platforms use highly complex deep learning algorithms to provide you a better experience. 

The more deep learning algorithms experience, the better they perform. Expect this technology to offer human-like suggestions and perform functions that no other technology could replicate. 

Autonomous Cars, Drones, and Driverless Delivery Trucks

The self-driving cars depicted in science fiction movies are becoming a reality. Some vehicles can comprehend stop signs, maps, and various other driving-related elements, which is only possible because of the deep learning algorithms. The algorithms evolve as they receive more data. As mentioned earlier, this technology is gaining human-like processing abilities as it can also recognize a stop sign smothered with snow. 

Pharmaceuticals and Medicine

From tumor diagnoses, various diseases, to customized medicines made especially based on every patient’s genome; deep learning can provide many benefits to medical and pharmaceutical companies. High-profile hospitals and clinics are also incorporating this technology as it helps streamline their cluttered procedures. 

Service and Chat Bots

Service and chatbots are handy tools for companies. Why? Because they are ideal for providing efficient customer service by responding to people’s complains and queries in time. Deep learning makes these bots more sophisticated, helping them provide helpful and intelligent responses to audio and text-based questions



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