In a recurrent neural network, the importance of LSTMs or long short-term memory networks should be emphasized because it works as its extension. LSTMs enable the recurring neural network to remember inputs over a long period and store them as information in its memory like a computer can. There are many interesting things about neural networks that programmers should know. If you want to know what are the different real-life applications of neural networks, read on below.
What Is A Neural Network?
Artificial neural networks are actually inspired and modeled by the real human brain. The human brain has different small units called neurons, that are connected to an extensive collective network. Each unit is relatively simple, but the whole network can solve even more complicated tasks when each neuron functions together. On the other hand, computers are also composed of networks that are made up of smaller units, much like the layers in a physical human brain. A neural network is a general term used to describe a class of artificial networks that mimics one or more natural human brain functions such as language, judgment, memory, planning, and thought. An artificial neural network can be thought of as a powerful supercomputer that operates by controlling inputs (or information) and producing output (or results) in response. In essence, it can be thought of as a control unit that takes information and processes it to come up with a programmed response. This function is what makes artificial neural networks such a fascinating tool. Take the example of a voice recognition software that recognizes a particular speech. The speech is fed through to the first input layer (computed voice recognition database), where it’s analyzed. The second input (or text) is then added to the second hidden layer, and so on until the desired output is obtained. The beauty of this system is that each voice can be separately extracted, with no concern for the relationship between them. The output layer only needs to be fed with the raw speech data to assist the artificial neural network operation. Once the desired output is obtained, it is passed on to the third input layer, which analyzes the speech more thoroughly.
Where Are Neural Networks Applied?
Today, neural networks are revolutionizing daily life and business, delivering amazing new levels of artificial intelligence (AI) to industries everywhere. These networks are being developed for several reasons, This includes improving the efficiency of machine learning and the ability of technology to solve day-to-day human challenges and activities. Neural networks are developed so a computer or system can work like a human brain. Once the neural network is trained based on given inputs, you can benefit from the desired results. Here are some real-life applications of neural networks you need to know about:
1. Speech And Voice Recognition
Speech recognition can be found in many applications today. Speech and voice recognition can be found in home automation, hands-free computing, video games, and virtual assistance. Just think of Siri and Alexa. These virtual assistants are made possible because of advanced neural networks. Platforms like Google and YouTube also add a voice search option to assist users.
2. Fraud Prevention
In finance, neural networks are used to determine fraudulent transactions. Some neural networks create systems where they study past account transactions and the frequency of the transactions to determine if it’s fraudulent or not. Neural networks also determine fraudulent transactions through the size of the transaction and the kind of retailer involved in the transaction. Also Read: Top 13 Best Voice Changer Apps For Android & iPhone in 2021
3. eCommerce
The neural network application in this industry focuses more on personalizing the user experience of a site visitor. Large eCommerce platforms use artificial intelligence to show related and recommended products that a person might be interested in purchasing. It also compiles product recommendations based on consumer behavior and past purchases.
4. Cybersecurity
Neural networks are also widely used to protect computers from viruses. Neural networks protect a computer from cyber-attacks by determining if a USB device is faulty or if it contains viruses or malware. It’s also used to exploit zero-day vulnerabilities.
5. Text Classification And Categorization
Text classification is mainly used in web search, information filtering, and language identification. Text classification and categorization can also be used to organize website content and documents on your system. For example, you can organize content by topics or manage them based on priority or urgency.
6. Stock Market Prediction
Many factors affect the performance of the stock market. A neural network can examine different factors and predict prices to help a trader decide on their next move. The development of these applications is still in the initial phase as the network should study a large volume of historical and market data to make a sensible and accurate prediction.
7. Marketing
Neural networks are also used in target marketing. When a marketer tries to define or identify a target market, market segmentation methods are used to divide potential customers into distinct groups based on criteria like consumer behavior, age, location, and other demographics. These neural networks can be programmed to engage with different segments in an appropriate and more personalized manner. Also Read: 13 Best Marketing Apps To Promote & Drive Your Business
Summary
Neural networks are valuable tools for industries, businesses, and individuals. For marketers, it can help them personalize strategies and encourage repeat purchases from previous customers. It can also help stock traders decide on their next move. Banks have been using neural networks for fraud detection and cybersecurity. You may not know you’re already using a system that uses neural networks. It can be found in speech and voice recognition apps on your phone or home control system. When you shop online, neural networks provide you with product recommendations based on your recent purchases or behavior. If you’re wondering why your Facebook feed is suddenly filled with ads about skincare products after purchasing a moisturizer from an online shop, then you’ve just witnessed neural networks at work.
