Learn how machine learning is making the purchasing process more customized and secure.

With every passing day, the use of machines is becoming essential for people who have a greater and more precise and automated reach.

Machine learning is increasingly popular by managing the fingerprints of companies that are running more and more accurate and fast.

In this article, we will see a bit about what is Machine Learning and how it is used in the market.

What is Machine Learning?

The Machine Learning technique is a specific AI strand that trains machines to learn from data. These machines have the ability to learn alone from large volumes of data through big data algorithms. These machines identify patterns in data and create intelligent connections, learning and performing tasks without human help.

The goal of this process is to predict responses more precisely and deliver the best result with less chance of errors.

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

Supervised: In this category, it is necessary the interaction of a human to control the output and input of data and if necessary, interfere in the training of the machine making comments for the learning and application in the next analyzes of the machine in question.

Unsupervised: In this category, machine learning is used against data that does not have historical labels. They use Deep learning to process complex tasks without human training.

What are the advantages of using the Learning Machine?

  • With unlimited data delivery from multiple sources, you can constantly review data and help message based on behavior. After being trained, the machine can identify more relevant variables and transmit certain information. It is also an effective way to automate internal company processes.
  • It is possible to process, analyze and forecast quickly the needs of the client, promoting a more customized experience for each moment or individual. This is because learning happens through past behaviors thus improving predictions based on new data.
  • Can be used to identify customer segmentation, or create micro-segmentation based on behavioral patterns. This type of learning helps to create a preventive approach to customer segmentation, thus guiding each one individually through the purchase journey.


Is there a difference between artificial intelligence, machine learning, and leed learning?

Although they work with learning and data analysis through machines, these three parts have their own characteristics and ways of working and presenting results.

Artificial Intelligence, for example, has the ability to mimic some human characteristics through visual perception and speech recognition. Everything you learn is based on or inspired by human characteristics or behavior.

In the Machine Learning technique, learning happens without actually being programmed, the machine adjusts itself to give answers according to the data already available for the analysis. In this technique, human intervention is not really necessary to make the changes, since the objective here is dynamic learning through existing data.

With more complexity than the Machine Learning technique, the Deep Learning subset is mainly used to refer to the more complex artificial neural networks. Using sets of algorithms that establish new, more accurate records for various problems with actions such as image and sound recognition, systems and recommendation, among many others.

Examples of Machine Learning application currently

  • Autonomous google chats (Essence)
  • Recommended offers like Amazon and Netflix (Day-to-day)
  • Know what the clients talk about you on twitter (Language rules)
  • Fraud detection

It is not difficult to see companies using the technique. Nowadays, sectors such as financial services already use Machine Learning to identify fraud or investment opportunities.

Marketplace and online stores mainly use to enhance the customer experience and fulfill wishes and needs through product recommendations based on previous purchases, or analyze purchase history and searches to promote items of interest thereby customizing the experience on the site.

Now that you already know a little bit about this technique, how about further customizing your customer experience and making the shopping experience safer? This is a trend for the next few years and many businesses are already adapting to this new phase.

So, did you like the article today? Already knew this technique? Come and tell us.

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