How Machine Learning Is Transforming Business

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Technological evolution is undeniable, since thanks to its advances, various activities require fewer resources, in addition to helping to improve work activities and saving time. However, behind the great computer creations is the ingenuity of people with great studies such as the Professional Master’s Degree in Technical Management of Data Science. Currently, there is a topic in the vast world of technology that may seem simple at first but is making great strides for the world: Machine Learning. 

What is Machine Learning? 

Before talking about the benefits of this tool or even applying it, it is important to understand its significance. Machine Learning is within the family of artificial intelligence. Its main function is to learn techniques that allow computers to learn; once this information is acquired, it will be stored as databases that will let in the future to identify patterns in order to create autonomous predictions in the future. 

Although Machine Learning is within artificial intelligence, it should not be properly confused with Artificial Intelligence. While the first one is focused on training a machine to learn from databases, AI attempts to learn and imitate human behaviour.

This ability to learn based on specific patterns has been practised by large companies for a long time. For example, the videos that appear on TikTok, the advertising on Google’s website, and Spotify’s playlists are thanks to the fact that you made the algorithm understand that you like certain specific content, therefore it learns from your actions taken and recommends content that can attract your attention. 

Basic Machine Learning algorithms

There are several different algorithms within Machine Learning that help in its training method. Below, you will find the most common ones:

  • Reinforcement Learning: Its main function is to develop an effective strategy based on its past experience, the objective of which is to optimise data. In short, the machine learns from its own experience, which will enable it to strengthen its analysis techniques. 

In reinforcement learning, there are variants of its functioning:

  • Agent: It is the model which receives the training and decision making.
  • Environment: The place where the agent will do its work. This environment is made up of present constraints and rules. 
  • State: The indicator of the environment, i.e., how the elements and variables are. 
  • Action: These are the possible decisions that the agent will take in the situations that arise.
  • Rewards or penalties: Depending on the actions taken by the agent, it will receive rewards or punishments, depending on whether his actions were correct or failed.
  • Supervised learning: This is a method of data analysis which uses prior learning based on a system of labels associated with the data. The previously found information allows computers to find information that is not visible to the naked eye. An example is a spam detector that labels an email as spam or not based on patterns it has learned from the email history.
  • Unsupervised learning: Unlike the previous one, algorithms from unsupervised learning have no prior knowledge. Such learning is confronted with a set of random variables, with the aim of finding patterns that allow them to be organised in some way. For example, in the field of marketing, they are used to extract patterns from massive social media data and create highly targeted advertising campaigns.  

Read: How Businesses Use Big Data For Data Reporting And Analytics

Benefits for your business

  • Since Machine Learning collects and stores data, it can help you to better understand your customers and target audience, in order to tailor your products and/or content to something that is of interest to them, which will help you both in marketing strategies and in decision making when launching a product.
  • The function of Machine Learning is to identify patterns. This association allows to automate processes, making the probability of human error almost null, thus, the analytical models can be generated on this basis to study data, as well as to learn from errors and take preventive actions.
  • With considerable amounts of data, these can be analysed in order to detect patterns and trends, for example, products that are most likely to be purchased by customers, so that they can be offered advertising content that might be of interest to them, such as offers.
  • As Machine Learning is constantly learning, it will be able to detect abnormal behaviour within computer systems, as well as offer the possibility of detecting possible financial fraud.

After you have learned more about Machine Learning and the advantages that can be obtained from this tool, you can denote that it will be quite sought after in the not-too-distant future, hence you can begin to consider investing in a professional in data science, or specialise in this field. However, keep in mind that being a tool that requires the best technological tools for its optimal development, as well as some investment.

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