In addition to optimizing various activities, Deep Learning can be used to better understand customers and improve their experience , as well as to reduce the margin of error in any activity, and even to detect fraud.
In this post we will tell you all about Deep Learning, which will allow you to learn more about process automation .
What is Deep Learning?
The first step to understanding what Deep Learning is is to understand what the term means. In its translation from English to Spanish, Deep Learning means “deep learning.”
This is a type of Machine Learning, zimbabwe email list which translates as “automatic learning”, but more evolved, which prepares computers to perform tasks that until then were only performed by humans.
Based on Artificial Intelligence (AI), Deep Learning improves the ability of machines to recognize, classify, detect, describe and perform numerous tasks .
The use of Deep Learning offers the possibility of improving and optimizing processes, making the daily life of companies and consumers easier and contributing to the delivery of better, faster and more accurate results.
How does Deep Learning work?
To fully understand what Deep Learning is, it is also necessary to understand how it works.
Deep Learning allows you to configure basic parameters related to data and information, and train a computer to learn by itself , using pattern recognition for this.
This recognition, in turn, includes issues such as image identification, voice, detection, predictions, among others.
In what situations can Deep Learning be applied?
Just as important as the definition of Deep Learning is knowing in which situations, under what conditions and at what times this Artificial Intelligence method can be applied.
Among the various applications for which Deep Learning can be used, we can mention:
Monitor and understand consumer behavior more accurately , identifying, for example, whether they intend to buy a particular product or service, or their emotions
Capture the needs of customers to offer solutions in a more timely manner and aligned with their needs
Improving the quality and efficiency of customer service with the enhancement of Artificial Intelligence chatbots
Perform facial recognition and thus increase security levels when people access different areas of a place.
Reducing the possibility of fraud in companies that use algorithms in their processes
Identify potential failures or errors in systems, software and processes in advance
Deep Learning Examples
The use of Deep Learning is not alien to our daily lives. A good example of this is the use of facial recognition to unlock the screen of a smartphone. The police also use this principle to recognize fugitives and wanted persons.
Virtual voice assistants such as Google Assistant, Cortana, Alexa and Siri also apply Deep Learning as a basis for their technology.
On social media , platforms apply this concept to analyze user interactions and behaviors in order to then improve the suggested offers and content they present to them.
Machine Learning vs Deep Learning. What is their difference?
It is not uncommon when researching what Deep Learning is, to come across another term: Machine Learning.
Machine learning is an AI application that teaches computers how to perform specific tasks based on the analysis of information .
