The development of technology and the process of implementing digital transformation have been changing the market, creating new opportunities and demands. In this scenario, companies’ understanding of technological tools, which are at their disposal, has an increasing impact on their performance. Among these tools, Deep Learning applications can be listed among the most important.

This is because, through this technology, companies are able to make important processes —such as the calculation of market data, the organization of tasks, and even the study of their target audience—much smarter and more accurate, which is obviously positively reflected in their performance.

Thanks to these characteristics, Deep Learning has been increasingly implemented in companies, so businesses less attentive to this market trend tend to be left behind.

Would you like to understand how this technology works? Read the article and discover the main applications of Deep Learning!

Deep Learning Concept

Deep Learning, a term that can be freely translated as deep learning, is nothing more than a Machine Learning application. As its name suggests, this concept aims to take Machine Learning to a deeper level, which makes room for software and applications to perform more complex tasks.

To achieve this result, Deep Learning makes use of the technology known as neural networks. An artificial neural network is understood as a system composed of several nodes, devices with computational power, which operate together to obtain broad computing power and, with this, to mimic the function of neurons in the human brain.

Thanks to these characteristics, Deep Learning is able to analyze patterns in a more complex way, identifying data and reaching results that other applications would not be able to.

Taking these facts into consideration, we can argue that Deep Learning is a branch of Machine Learning that makes use of advanced computational power to analyze complex data in search of patterns, allowing it to perform strategic functions for companies and individuals.

Technology applications

Given its functionalities, the technology is able to perform a number of useful tasks, which makes the management of a company and the execution of its commercial activities simpler and more efficient. Continue reading and understand some of the applications of Deep Learning!

Natural Language Processing (PLN)

Natural Language Processing can be described as a concept developed to enable communication between the human being and the machine. Simply, we can say that technology uses algorithms to provide software with the ability to understand a person’s communication and even interact with them, performing tasks or presenting results.

Identification of patterns

Through Machine Learning, the software has the ability to study data in search of patterns, allowing them to learn from their own discoveries, thereby increasing their efficiency. Deep  Learning, in turn, aims to take this concept deeper, making room for a number of functions and possibilities.

Deep Learning practical application

Deep Learning applications are many, so thanks to the features that were mentioned in the previous topic, the technology can be used in several different ways. To better understand how it works in practice, we’ve set some examples from its implementation. Follow!

Virtual Personal Assistants

Virtual Personal Assistants, such as Siri and Cortana, are already part of many people’s daily lives, simplifying tasks such as:

  • conduct searches in search engines;
  • send messages and make calls;
  • online shopping and service scheduling;
  • organize alarms  and  reminders.

It is important to highlight that this technology can also be used in the corporate world, optimizing task management and monitoring of activities. In addition, when combined with the Internet of Things (IoT), its functionalities expand.

The big issue is that to operate more efficiently, Virtual Personal Assistants use Deep Learning applications.

Recommendation Systems

Nowadays, when we access websites and blogs, it is common for ads like  Adsense, aligned with our search history, to appear. In addition, when entering digital retail platforms, a person will receive a number of suggestions based on their latest purchases.

This is thanks to so-called Recommendation Systems. They can be described as Artificial Intelligence applications that study user behaviour and, based on it, deliver results of interest to you.

For Recommendation Systems to operate properly, they need to use deep learning solutions.

Sentiment analysis

Understanding a person’s feelings, and their impressions about certain topics are fundamental to the execution of various processes. As an example, we can cite individuals’ reactions to Adsense ads—a positive reaction is necessary for the user to click on the ad, and even for them to purchase the product or hire the service.

Through Deep Learning applications, specialized software can study people’s behaviour patterns in relation to various types of ads and advertisements. With this, they become able to learn which models are most successful and still identify the factors of their success or failure.

Image analysis

Another very useful feature of Deep Learning is how it optimizes image analysis. Thanks to its functionalities, the software can identify several patterns, which can be used, including to diagnose diseases. The technology can also be used in facial recognition and biometrics systems, optimizing the safety of people and companies.

One of the most interesting factors about Deep Learning is that technology has the potential to complement other innovations, thus creating a true universe of solutions and possibilities. Taking this fact into consideration, it is easier to realize the impacts and importance of technology.