Concept of Machine Learning and Deep Learning

Machine Learning and Deep Learning – Within the Artificial Intelligence (AI) field. We find the concepts of Machine Learning and Deep Learning. We will try to clarify these ideas and the differences between them.

As we saw in a previous blog post dedicated to Artificial Intelligence, its use has become necessary for many companies since it can positively impact them.

You can consult the cited article at the following link: https://omega2001.es/inteligencia-artificial-en-las-empresas/

Machine Learning and Deep Learning

Both purposes are to generate models that allow us to predict and find patterns in the data.

Machine Learning

It began to advance in the 80s of the 20th century.

The continuous technological advances, and the increasing power available for data processing and treatment, have contributed to its development and use in diverse fields.

Machine Learning or Automatic Learning is a branch of AI that aims to develop a series of techniques that allow computers to learn by themselves.

It is necessary to enter a large amount of data to enable learning.

In the case of Machine Learning, this data must be structure and categorize. Algorithms are use to analyze the data, learn from it, and enable the computer to make decisions based on everything it has learned.

Algorithms are rules that will give the computer the necessary instructions to make the appropriate decision or execute the desired task.

The algorithm can be optimized through human intervention. Indicating to the system when it has made a mistake in the classification and telling it how to assign the categories correctly.

Fields of Application of Machine Learning

1. Mail classification as spam or not spam.
2. Customer service through chatbots.
3. It is use on streaming platforms like Netflix to recommend new content base on our tastes.
4. In the marketing field, it is use to send advertisements or personalized offers based on the interests of potential customers.
5. It can be use for the detection of cybercrime, such as for the identification of fraudulent transactions.

6/ In medicine, it can help diagnose specific ailments.

7/ Companies can use it to predict certain aspects of their activity, helping them make the right decision.

Deep Learning

It is also called deep learning, and it was develop from the year 2010.

Moreover. It can say that Deep Learning is an evolution of Machine Learning, which is use for more complex tasks and requires a much larger volume of data.

For this reason. And because it is much more expensive to implement, it is usually used less and only in some particular regions.

However. Deep Learning uses high-level algorithms to generate advanced learning. To do this, it mimics the existing neural network in the human brain.

It structures the algorithms in various layers, creating an artificial neural network capable of learning and making decisions on its own.

It is, therefore, much more complex and advanced than Machine Learning, reducing the margin of error and increasing the precision of the conclusions.

But, on the other hand, it needs a much higher investment of resources.

Application Areas of Deep Learning

1. Recognition and categorization of images. It is use to tag photos to classify objects and people within an image.
2. Customer service. Deep Learning allows a better understanding of natural human language, makes the dialogue much more effective and offers more precise solutions or responses.
3. It is the technology used by virtual assistants, such as Siri, Alexa or Google Assistant.
4. Automated content creation and more accurate machine translations.
5. The security of computer systems will be much more lavish through this technology.
6. Autonomous driving. It allows vehicles to operate without the need for human intervention.

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