Deep learning within artificial intelligence?

Before you read this article and don’t know what machine learning is yet, click on this word to read this blog from us. Machine learning is to mimic human interaction and continue to better understand our users. It recognizes familiar faces, identifies what’s on a photo, and identifies which photos come from different parts of the world, such as different countries, different cultures, or even different eras.

The main subfield of machine learning is deep learning and uses algorithms to treat a function in the structure called artificial neural networks.
Deep learning is therefore a development of machine learning. The term deep learning comes from the studies of the structure of neural networks and their interaction with human brain cells.

When people use the term “deep learning”, they refer to deep artificial neural networks. These are algorithms that have set new records in areas such as deep learning, deep enhancement learning and machine learning.
Deep learning is a sub-area of ​​machine learning that deals with algorithms inspired by the structure and function of the brain, so-called artificial neural networks. The concept is then based on the idea of ​​creating and using artificial neural networks to make decisions based on a given set of data.

The first company to truly develop deep learning is Google Brain, which was founded in 2009. Google Brain eventually led to the creation of the world’s first artificial neural network, the Google Brain Network.
For example, deep learning is the basis of DeepMind’s well-known AlphaGo algorithm, which defeated former world champion Lee Sedol in Go in early 2016.

So what is deep learning within Artificial intelligence?
– Artificial Intelligence is when a computer can perform a series of tasks based on instructions
– Machine learning is the process of collecting and learning data to complete a task more accurately and accurately.
– Deep learning develops as large neural networks are built and trained with more and more data. This also increases performance.
Neural networks are therefore much more powerful than one would think because of their self-learning.

There are two terms that are often used interchangeably to describe software that behaves intelligently: Deep Learning and Machine learning. Sometimes it is about Natural Language Processing (NLP), but in fact this means nothing more than applying artificial intelligence (or through machine or deep learning) for language.
As you may already know, deep learning is used wherever artificial intelligence exists and has a wide range of applications in different areas, such as logistics, manufacturing and process industry, financial sector, healthcare, medicine or pharmaceutical industry, retail and wholesale, the construction, agriculture, food or feed producers, government, municipalities and education, and many more industries.

In accordance with the principles of machine learning, deep learning is essentially the process of entering huge datasets into a knowledge base, which is then made available to a computer to use as a “knowledge base” for interpreting new data. It focuses on the specific tools and methods that enable the implementation of machine learning and the subsequent solution of more or less problems that require both human and artificial thinking.

The difference between the two is that machine learning needs guidance to complete a task. Machine learning is a concept for analyzing data and provides excellent recommendations based on learning points. In machine learning, a programmer had to repair the algorithm if the results were inappropriate while a deep learning model does its job without the intervention of the programmer. Strange idea huh?

Deep learning algorithms use basic machine learning techniques to solve complex real-world problems using neural networks similar to those used in human decision-making. In deep learning, a deep artificial intelligence neural network uses complex algorithms to provide a high degree of accuracy in solving complex problems such as speech recognition, image processing and speech processing. Deep learning is a new form of artificial intelligence / artificial intelligence or AI in computer science.

For this reason, RPA is increasingly popular in various industries such as logistics, manufacturing and process industry, financial sector, healthcare and pharmaceutical industry, retail and wholesale, agriculture, food or feed producers, construction and government and municipalities where many tasks are repetitive but also more and more in-depth analyzes are needed.

Curious about what this new technology can mean for your company?
Then take a look at our solutions page with industry-specific solutions or contact us!

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