Have you ever wondered how Google Assistant or Apple’s Siri carry out your voice command? Do e-commerce websites show you advertisements for goods you’ve previously searched for?
If you’ve been curious about how everything fits together, Artificial Intelligence (AI) works in the background to provide you with a rich customer experience. The key to teaching machines to respond to instructions the way humans do is Artificial Neural Networks (ANN).
What is a Neural Network?
An artificial neural network in information technology (IT) is a system of hardware and/or software that is patterned after how neurons in the human brain function.
Artificial neural networks (ANNs), also known as neural networks, are a type of deep learning technology that is included in the artificial intelligence (AI) category.
These technologies are often used in the business world to solve complex signal processing or pattern recognition problems.
Since 2000, some notable commercial applications have included handwriting recognition for processing checks, speech-to-text transcription, data analysis for oil exploration, weather forecasting, and facial recognition.
What exactly is an Artificial Neural Network?
These are computer simulations that draw inspiration from the human brain. Artificial intelligence has been used in many recent developments, including voice recognition, image recognition, and robotics.
They are computer simulations that are based on biological principles and are used to carry out specific tasks like – Pattern recognition, Clustering, and Classification.
It is a network of artificial neurons designed with biological inspiration to carry out particular functions. The next significant development in the computing industry is thought to be these biological computing strategies.
5 Uses for Artificial Neural Networks
● Social Media
Social media makes immense use of artificial neural networks.
Take Facebook’s”People you may know”feature, for instance, which suggests users send friend requests based on potential familiarity.
The people you might know are determined by using Artificial Neural Networks, which examine your profile, interests, current friends, their friends, and various other factors to determine who you might know.
Facial recognition is a typical use of machine learning in social media.
Convolutional neural networks are used to find approximately 100 reference points on the subject’s face and then compare them to points already present in the database.
● Marketing Industry
Based on your previous browsing history, e-commerce sites like Amazon and Flipkart will suggest products to you when you log in.
Similar to how Zomato, Swiggy, etc. will show restaurant suggestions based on your needs and requirements and previous order history if you love pasta.
It is done by implementing personalised marketing, which is true across all new-age marketing segments, including book sites, movie services, hospitality sites, etc.
The marketing campaigns are then customised based on the customer’s preferences, dislikes, previous purchases, etc. using artificial neural networks.
● Health care services
Algorithms that can detect cancerous tissue at the microscopic level with the same accuracy as trained doctors are trained using artificial neural networks.
Using facial analysis on the images of the patients, various rare diseases that can manifest physically can be detected in their early stages.
Therefore, the widespread adoption of artificial neural networks in the healthcare sector can only improve the diagnostic skills of healthcare professionals and, in the long run, raise the standard of healthcare globally.
● Personal Assistants
You all have probably heard of Siri, Alexa, Google Assistant, and other virtual assistants thanks to your smartphones, I’m sure.
These are personal assistants that use speech recognition and Natural Language Processing to converse with their users and create responses in line with their needs.
Artificial neural networks are used in natural language processing to manage many of these personal assistants’ tasks, including managing language syntax, semantics, correct speech, ongoing conversations, etc.
● Prediction for the Stock Market
Market risks are present for investments. The highly unpredictable stock market makes it nearly impossible to anticipate future changes.
The constantly fluctuating bullish and bearish phases were unpredictable in the era before neural networks. But what caused the change?
A Multilayer Perceptron (MLP) is used to make a successful stock prediction in real time. Each layer of nodes in the MLP structure is completely connected to the layer below it.
When developing the MLP model, historical stock performance, annual returns, and non-profit ratios are taken into account.
Artificial Neural Network-based careers
Edology may soon witness more developments in the use of neural networks, given how quickly businesses are adopting AI and machine learning at the moment.
Users everywhere will have access to a wide range of personalised options thanks to AI and machine learning.
Artificial Neural Networks, for instance, can enable the enhanced, customized experience that all mobile and web applications strive to provide you with based on your search history.
- Test engineer
- Research scientist
- Software engineer
- Data engineer
- Machine learning engineer
- Deep learning engineer
Additionally, neural networks will be used in everything you can think of, including physics, agriculture, medicine, and research.
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