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Machine learning and deep learning: how are they different?

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For the past decade, technology has had a pretty clear focus: making things work smarter and with less human effort.

In this context, the concepts of machine learning (ML) and deep learning (DL), practices within the field of artificial intelligence (AI). Big companies like Google, Twitter, Facebook and Pinterest use machine learning or ML to offer you a better experience, so even if you haven't noticed it before, you live with this type of technology on a daily basis.

What is machine learning?

First of all, the machine learning this technology is also known as machine learning or of the machines.

Machine learning is a branch of AI that seeks to equip applications with intelligence through data analysis, allowing them to learn and improve their accuracy over time.

Applications use trained algorithms to identify patterns within the massive amounts of data they process and subsequently generate learning. Based on previous experiences, applications are able to make decisions and make predictions on new data.

An application of the machine learning Very common is the personalization of marketing, where consumer preferences and behavior are analyzed and then deliver promotions that really fit their profile.

What is deep learning?

The first thing you should know is that deep learning, in Spanish, means deep learning.

He deep learning is a branch of machine learning and goes one step further: it uses high-level algorithms with the intention of imitating the structure and functioning of the human brain through artificial neural networks.

Thanks to this technology, the deep learning manages to automatically modify itself, achieving advanced learning and performing complex tasks that would not be possible through rule-based programming. In simpler words, machines and applications learn by themselves from errors and information received.

An example of this technology can be found on Facebook, that uses facial recognition to detect and locate faces.

Differences and Similarities Between Deep Learning and Machine Learning

Before going into details about their differences, it is important that you are clear about the following:

  • ML and DL come off the Artificial intelligence.
  • Deep learning is a more advanced category of machine learning.
  • Both are increasingly penetrating the cloud computing technologies, contributing to the business scalability.
  • One technology does not replace the other, in fact, they become a more powerful tool when combined.

Now, the most important difference that you need to focus on is this: a computer with machine learning it needs to be guided during learning, since it is from practice and repetition that it manages to generate patterns of behavior.

On the other hand, with deep learning (in Spanish, deep learning), this is not the case. In this case, the computer has the ability to learn by itself each time it obtains new data. Also, learn from mistakes and avoid repeating them in the future, making the process more efficient and faster over time.

If you are interested in Artificial Intelligence, Codster is an experienced company in technological solutions that will help you during the process of creating and implementing apps and digital platforms based on ML and DL protocols. 

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