Advancements in technology are changing the world at a higher rate than people ever thought. It has changed how people do their things, including how they communicate or interact. Though many technologies have come and gone, there’s one technology that seems to hold the future of technologies. That’s machine learning technology.
Machine learning technology has been in use for quite some time, and all indications show that this technology might remain relevant for the foreseeable future. With machine learning, people build systems that allow computers and computerized devices to learn how to do things themselves rather than teach them how to perform those tasks. The most common form of machine learning used in different sectors is deep learning.
What Is Deep Learning Technology?
Deep learning is a technology that helps computers build a complex mathematical structure, referred to as a neutral network, based on vast quantities of data. While machine learning is a general technology where computers use algorithms to analyze data and learn from it, deep learning is a subfield or extension of machine learning. It allows computers to implement machine learning through long-short memory (LSTM) artificial neural networks or the human brain.
In simple terms, deep learning technology works by attempting to mimic the human brain, allowing computers to learn from large quantities of data. For more information about LSTM, you can read full article here.
What Is The Importance Of Deep Learning Technology?
Before the invention of deep learning technology, people used traditional machine learning methods such as regression, decision trees, and Bayes’ probability theorem to analyze data. These methods couldn’t be applied directly in the analysis of raw data because they lacked a preprocessing extraction feature. Extraction is a complex feature and requires a better understanding of the problem domain in order to get the desired results.
On the other hand, deep learning uses artificial neural networks that don’t require feature extraction. It helps computers learn from raw data and allows them to produce accurate results.
Also, with deep learning technologies like chatbots, businesses and other organizations could communicate efficiently with their customers. Deep learning also provides cost-effective communication solutions because it eliminates call-waiting queues. This helps address customers’ issues as they arise and helps improve customer service.
How Is Deep Learning Changing The World?
Machine learning is transforming the world as it’s positively impacting people in almost every aspect of their lives. Here are some examples:
1. Self-Driving Cars
Self-driving cars, which are built to use machine learning algorithms, are one of the most and recent applications of deep learning technology. This self-driving or autonomous car technology may be the biggest societal revolution since the industrial revolution.
It’s believed that autonomous cars could help solve many road problems, like traffic delays and human errors caused by accidents. According to a report, more than 90% of road accidents are caused by some type of human error. This is because many accidents happen when a driver becomes tired, gets ill, or gets stressed.
Autonomous vehicles aren’t prone to these factors, so the number of car accidents on the road may be reduced or eliminated with the use of self-driving cars. These autonomous cars could also detect objects around the car and the distance between the car itself and other vehicles, which would also help reduce road accidents.
2. Virtual Assistance
Virtual assistance is another area where deep learning technology has gained popularity in the modern world. Virtual assistants have come to make work easier and only perform what they’re directed to do. Most virtual assistants are found in online training sites and communication apps.
The main application of deep learning technology in a virtual assistant is voice recognition and voice-to-text recognition. Each time you interact with these virtual assistants, they get an opportunity to learn more about your voice so they could be able to recognize it during your future interactions. This allows them to provide you with a secondary human interaction experience. Virtual assistants use deep learning technology to understand your command and translate your voice to text, especially when making notes for you.
Deep learning technology is also trending in the healthcare world. Medics use wearable sensors and gadgets to transmit patient information about their overall health conditions, such as heartbeat rate, sugar levels, and much more.
Medics use this information to diagnose their patients and provide any other necessary assistance. The use of deep learning technology in healthcare also helps healthcare professionals analyze patient data. This helps recognize trends that could enhance medical care and diagnoses.
4. Fraud Detection
Another critical area where deep learning technology is applied is the detection of fraud in the banking and retail sectors. With many people shopping online and the increase in online banking, which have created more opportunities for fraud, there’s a need to use modern technology to counter-fight it.
Fraud detection and prevention with deep learning becomes possible as this technology uses algorithms to learn from fraud incidences in the past. Thus, it becomes much easier to recognize such frauds in the future. Also, deep learning technology could help detect sophisticated fraud incidences that a human can’t detect.
Deep learning is one of the recent technologies, and it’s believed that it’d continue to improve the quality of life by allowing people to complete complex tasks more efficiently and with less time. Furthermore, the interaction with deep learning technology could help societies evolve with the use of autonomous vehicles, virtual assistants, healthcare, and much more, as you’ve seen above.