{"id":3501,"date":"2019-06-26T22:45:33","date_gmt":"2019-06-26T22:45:33","guid":{"rendered":"https:\/\/www.latamdigitalmarketing.com\/blog\/?p=3501"},"modified":"2019-08-08T22:10:33","modified_gmt":"2019-08-08T22:10:33","slug":"machine-learning-technologies","status":"publish","type":"post","link":"https:\/\/www.latamdigitalmarketing.com\/blog\/en\/machine-learning-technologies\/","title":{"rendered":"Machine Learning Technologies | The secret behind algorithms"},"content":{"rendered":"

It is no secret that one thought has crossed our mind on many occasions: We would like to predict the near future of our company, or to know what our customers want. This is possible with Machine Learning.<\/p>\n

Companies must understand that information is the greatest resource they have, so databases are their most valuable resources.<\/p>\n

By knowing the information of its users, you can predict consumer behaviors.<\/p>\n

And by detecting those behavioral patterns, we can plan what measures need to be implemented.<\/p>\n

Machine learning<\/h2>\n

Before, we used to think of an Artificial Intelligence (AI) of robots that solved problems for humans. But today, it exists as process automation, and data collection that we apply to company projections.<\/p>\n

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Machine learning, was born as an ambitious idea of \u200b\u200bAI in the 1960s. To be more exact, it was a subdiscipline of AI, a product of computer science and Neuroscience.<\/p>\n

What this branch intended to study, was the recognition of patterns (in engineering processes, mathematics, computing, etc.) and learning by computers. At the dawn of AI, researchers were eager to find a way in which computers could learn only based on data.<\/p>\n<\/blockquote>\n

We work in probabilistic reasoning, statistics-based research, information retrieval, neuromarketing<\/a>. By joining all this, is created a profile style of our customers.<\/p>\n

\"advanced<\/p>\n

In this way, with AI, we are able to create alerts and projections once you recognize patterns that users have had and others go in the same line.<\/p>\n

Nowadays, companies know that decisions are made based on data. This is why, the better the information, it will offer more value to perform the projection.<\/p>\n

Netflix, Real Case in Machine Learning Technologies<\/h2>\n

\"netflix<\/p>\n

Netflix is a great example: We understand that Machine Learning is born from artificial intelligence, and seeks to create an effect in its database.<\/p>\n

Through different algorithms, as well as lessons learned from other users, it is capable of predetermining profiles. This is why sometimes, it recommends movies that it thinks we would like, because other people have seen it.<\/p>\n

Even in its last upgrade, it decided to show it as a percentage, where it tells us how close or near it is to our preferences.<\/p>\n

This is why with Machine Learning, Netflix tries to personalize your experience, based on your preferences and those of similar people.<\/p>\n

The algorithm learns the things you like, and based on that, selects a flow of information (in this case movies and series) to display.<\/p>\n

Consider these ideas for Machine Learning<\/h2>\n

Now that you know that you have no limit to apply the Machine Learning to different aspects of your company, we leave you a list of ideas that you can implement:<\/p>\n