A technique of Machine Learning, Deep Learning is a field of Artificial Intelligence (AI) that aims to imbibe human brain function in data processing machines. The way the human brain works serves as the foundation of deep learning which is also called deep neural learning.
Data processing is a significant field and deep learning helps in processing vast amounts of data with the help of identified and verified patterns established by the human brain. A revolutionary technique of machine learning, deep learning has helped the field of technology advance manifold. A deep learning example is the use of voice assistants.
The rise of deep learning in AI has helped the digital domain excel and evolve unstoppably. Presented with unsupervised learning, the data is processed through the machines (computers) and deep learning algorithms are formulated in the process. This leads to the interpretation of data and identification of patterns that help machines work according to the human brain.
Back when Warren McCulloch and Walter Pitts produced a computer machine on the lines of the human brain and its neural functions in 1943, the origin of deep learning emerged. Ever since then, the concept of deep learning has evolved over the centuries.
Deep neural networks are made of digital nodes that act like neurons that together constitute the human brain. Layers of such nodes are aligned together that facilitates the concept of deep learning. As a signal is transferred to one node, it further travels to other nodes that link each other.
A set of signal inputs travel across these nodes that lead to a neural output as a result of algorithms and patterns established by the machine (computer). As massive data is processed through this artificial neural network, durable and giant hardware is required to support such an activity.
A set of mathematical calculations and algorithms come together to give rise to deep learning methods. As the nodes are imbibed with unsupervised learning, they are trained to work like a human brain and perform actions with accuracy and speed.
Even though the working of deep learning is an enormous topic to learn, we can read through the various applications of deep learning in artificial intelligence that will help us to understand the concept in a better manner.
Ever seen your computer asking you to re-enter a captcha or a character text in order to prove that you are not a robot? Well, deep learning is the one working behind this character text creation.
One of the deep learning applications is character text generation that automatically generates text and presents it on the screen. By identifying where to generate a text or not, deep learning works like a human brain and makes use of ‘deep’ layers of nodes that share a signal for this purpose.
Trained to automatically generate texts, captchas can be seen everywhere in today’s digital world. From every log-in that we perform to every sign-up we do, captchas stand strong for testing our intelligence.
That’s right! Deep Learning is in the healthcare industry too. From the diagnosis of disease to detection of the suitable treatment, deep learning works like a human brain and functions with the help of the artificial neural networks formed by digital nodes.
This helps the technological equipment to help doctors to perform their jobs well. Deep Learning has taken over the partially skilled ability of doctors to diagnose a disease. Rather, it has facilitated the accurate diagnosis of diseases that a patient is suffering through.
What’s more, the concept of deep learning can also help doctors to detect any possibility of diseases that can occur in the future. This has helped the healthcare industry to excel and advance substantially in the past decades.
(Must check: What is Healthcare Data Analytics?)
In the field of digital marketing, customer feedback has become an important component. In the contemporary scenario, companies intend to gather as much feedback and responses as possible in order to analyze the popularity of their brand and improvise accordingly.
Deep learning helps companies to analyze the responses of customers and detect the emotions hidden behind their words or feedback. This helps the corporations to analyze the performance of their brands and rectify their mistakes.
One of the most substantial applications of deep learning, customer feedback has made it possible for companies to reach out to a massive audience in an effective manner as opposed to the traditional ways.
Quite similar to customer feedback, deep learning also helps filter ‘aggressive’ or ‘obscene’ comments on social media platforms. This is done by analyzing the words and detecting the human emotions hidden behind such comments.
Further, deep learning helps social media platforms like Instagram and Twitter to regulate hate speech and assists in maintaining harmony among netizens. As social media has escalated into a mass media of massive importance, filtering aggressive and obscene comments is highly important for creating a productive virtual environment for people to connect, share, and flourish.
In addition, deep learning also helps social media platforms to interpret data and recommend people to each other.
Another use of the deep learning technique can be witnessed in the process of image coloration. Yes, you read it right. Deep learning has now made it possible to add color to otherwise black and white photographs.
As opposed to the traditional techniques that relied on humans to perform this task manually, the process of image coloration and addition of vibrant hues to black and white photos can be done by machines in the contemporary scenario.
Working along the lines of the human brain and neural networks, the applications of deep learning in image processing allows computers to learn about colors and establish algorithms that let them fill color.
This application is the topmost application in terms of popularity. Why? Well, deep learning is exactly what helps you to stream popular shows and songs on online streaming platforms.
Platforms like Spotify and Netflix make use of the technology of deep learning that lets them filter videos, shows, and songs as per your watching experience. Perhaps if you have seen a movie starring Brad Pitt, then your Netflix account is likely to show you more movie suggestions starring Brad Pitt.
Thanks to deep learning, one can experience personalizations based on their streaming choices and experiences so far. So the next time you hear a song and similar songs get lined up in the queue, remember that deep learning is working behind the stage.
(Most Related: Introduction to Deep Learning and Its Applications)
Self-driving cars technology is a striking feature of the automobile industry that has taken everyone by surprise. How wonderful it is to run a self-driving car and not needing to drive the car yourself! Deep learning has made self-driving cars possible that has eventually become the talk of the town.
Cars are being designed in a way that makes them work like a human brain owing to the artificial neural networks. With many companies working towards this purpose, cars are likely to work on the streets by themselves without needing any human assistance.
A revolution in itself, automatic cars are the future of deep learning as it continues to excel and advance.
Have you ever tried to find what makes virtual voice assistants like Siri and Alexa work? What makes them follow your orders and do as told? If yes, deep learning is your answer.
Deep learning has facilitated the imbibing of human brain values and functions in computers that make them perform tasks as they are told to do. Voice assistants like Siri and Alexa talk to you and do as told because the deep learning technology is making them do so.
So the next time when you say, “Hey Alexa, call mom.”, think of deep learning that is the master of this magic!
Fake news is highly crucial in the field of contemporary journalism. While the digital domain has made sharing of news possible at a rapid speed, fake news has emerged in the process becoming a major obstacle in true journalism.
While it is inevitable to stop people from posting fake news on virtual platforms, it is certainly not impossible to restrain fake news from reaching out to people. This means that fake news can be identified and pulled down as soon as computers operated by deep learning recognize fake news.
The use of fake news detection technique is rather useful in the contemporary scenario where fake news and rumors spread like wildfire. By verifying news and checking the facts, deep learning works like a human brain and helps platforms to pull down any such news content immediately.
Last but not the least, deep learning is also useful in facilitating customized search results. How? Let’s understand. Ever searched for a product on an e-commerce site and discovered its advertisements on other platforms too?
This is because deep learning displays customized search results which makes you look for products that it believes will be useful for you.
As opposed to the tiresome process of looking for 1000 options and then spotting the right one, deep learning has made the whole process a lot easier. Perhaps one can now enjoy customized search results and enjoy surfing online.
To conclude, deep learning is a subtype of machine learning that further belongs to Artificial Intelligence. Empowering computers to perform and act like a human brain, the deep learning technique is made up of multiple artificial neural networks that pass signals to one another converting inputs into qualitative outputs.
(Recommended blog: Machine Learning Applications)
Numerous applications and advantages of deep learning can further be used to understand the concept in a better manner. From automatic cars to voice assistants, deep learning is present everywhere making our lives easier and more efficient day by day.
6 Major Branches of Artificial Intelligence (AI)READ MORE
Reliance Jio and JioMart: Marketing Strategy, SWOT Analysis, and Working EcosystemREAD MORE
Top 10 Big Data TechnologiesREAD MORE
8 Most Popular Business Analysis Techniques used by Business AnalystREAD MORE
Elasticity of Demand and its TypesREAD MORE
What Are Recommendation Systems in Machine Learning?READ MORE
An Overview of Descriptive AnalysisREAD MORE
Deep Learning - Overview, Practical Examples, Popular AlgorithmsREAD MORE
7 Types of Activation Functions in Neural NetworkREAD MORE
What is PESTLE Analysis? Everything you need to know about itREAD MORE