Machine Learning: What is it and how does it influence digital marketing?

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Machine learning may seem futuristic, but there are endless applications of it today, even in digital marketing. Understand everything about the topic and how it impacts the future and current scenario.


Imagine being able to generate models that analyze large and complex data quickly and automatically to deliver the results you need on a large scale.

That's what machine learning does. This powerful technique is becoming increasingly popular with the digital transformation of companies.

With accurate data models, companies are better able to hong kong phone data identify profitable opportunities and avoid dangerous mistakes.

And not only that. The advantages of using this strategy are many and can even help you with the process of prospecting clients and selling your service or product.

That is why its use has such an influence on the success of digital marketing .

In this article you will discover:

What is machine learning?
Advantages of the strategy;
Differences between artificial intelligence, machine learning and deep learning;
Evolution of machine learning;
Folk methods;
Machine learning in digital marketing;
Future of strategy.
What is machine learning?
The very translation of the term "machine learning" gives an indication of its meaning. This technique encompasses the idea of ​​machines that have the ability to learn on their own from large volumes of data.

But how do they do it?

Using algorithms and big data, identifying data patterns and creating connections between them to learn how to execute a task without human help and intelligently.

These algorithms use statistical analysis to predict responses more accurately and deliver the best predictive result with less chance of error.

This technology can be separated into two main categories: supervised and unsupervised.

Supervised algorithms are those in which humans need to interact, controlling the input and output of data, interfering in the training of the machine and making comments on the accuracy of the predictions. The machine then applies what was learned in its algorithm and moves on to the next analysis.

On the other hand, in the unsupervised category , algorithms use deep learning to process complex tasks without human training.

We will talk a little more about these categories in the topic "popular methods".