Machine Learning Algorithms: How Do They Work

Have you ever heard of machine learning? How do machine learning algorithms work? How can we exploit them in the company? We have all always been fascinated by machines equipped with artificial intelligence. Does that mean machines can learn? Can we use them in our favor, or will they dominate us?

Even if Kubrick or Asimov would have liked it a lot (or maybe not), the answer is no. Algorithms capable of learning are indeed used in all fields, and many have become invisible because they have now become part of our daily life and are increasingly used by companies. But we can tell you with certainty that they are changing the world, and not everyone realizes it.

They are also the fortune of companies that operate on the web and that have made machine learning their fortune by becoming a leader in the world.

If you don’t know what it is and you are interested in understanding how machine learning algorithms work, take 3 minutes to read this article.

 What Is The Definition Of Machine Learning?

Let’s start with the general meaning. What is machine learning? As Wikipedia says, it is a branch of artificial intelligence that collects different methods developed in the last decades, such as computational statistics, pattern recognition, artificial neural networks, adaptive filtering, dynamic systems theory, image processing, data mining, adaptive algorithms, etc.

In simpler words, it is about the ability of “programs” to make themselves more efficient by learning and processing information. They are, therefore, machines that learn from experience and improve as it increases.

What Is Machine Learning For?

What do we do with all these learning programs? The development areas are different; we start with software to get to Smart Cities.

To give a practical example, we can talk about e-mail spam filters. These are based on machine learning systems that learn to intercept messages and delete them before they reach users and become potentially dangerous.

Tesla’s self-driving cars learn to recognize their surroundings through sensors and adapt their “behavior” according to their situations.

How Many Types Of Machine Learning Does A Machine Have?

A machine can have different types of learning algorithms:

  • Supervised: it uses the experience of the past (regression/classification) and based on this, it determines its own “intelligence.”
  • Unsupervised: acts individually: identifies hidden similarities and structures within the data (clustering).
  • Partially supervised: it is a middle ground between the first two, and it is also the most common situation because tagging all data is very expensive in terms of time and money.
  • With reinforcement: The algorithm has an evaluation system that aims to maximize it.

Taking, for example, the idea of ​​teaching an algorithm to recognize the image of a cat, we provide it with a series of pictures of cats and tell it that those images are just images of cats. Pictures of different objects or animals will be marked with a “not a cat” label. The speech changes with unsupervised algorithms where instead, human beings do not classify the data, and the machine has to extract the information from the data.

Will Machines Dominate Us As In A Space Odyssey?

Artificial intelligence that goes bad is perhaps the most popular cliché in the history of science fiction. However, today’s reality is very different, although many people are still skeptical about the possibility of living with “good” thinking machines.

Who knows if Stanley Kubrick in 1968 with a Space Odyssey would have ever thought that machines would one day dominate the world. Certainly, his HAL 9000 computer could, especially thinking it could be disabled or destroyed.

The speech is complex, and certainly, there are doubts about the dangers of artificial intelligence. The main problems have arisen because these machines tend to resemble their creators or learn based on past information, leading to erroneous behavior or assertions.

In any case, there are currently no real dangers that machine learning can bring big problems such as the extinction of the human race, and we can be calm.

How Can You Use Machine Learning In The Company?

The advantages of machine learning in the company are many:

  • decision-making speed: algorithms can automate decision-making processes
  • adaptability: artificial intelligence can operate in real-time
  • programmability: the algorithms can achieve a high degree of automation
  • complexity: they can analyze huge streams of data that are beyond human capabilities
  • efficiency: they enable the formulation of adequate plans and forecasts while reducing costs
  • productivity: they allow you to achieve better results based on the opportunities and risks identified

Entrepreneurs who care about innovation shouldn’t do without machine learning to improve their business processes. Google Cloud, in this case, offers a valid infrastructure with specific hardware accelerators.

The fields where it can be integrated are all from marketing to industry, passing through medicine.

What Is The Future For Machine Learning?

In recent years, companies have made great strides in developing machine learning applications. Just think of large companies such as Google, Facebook, Amazon, Tesla, or many others that use big data to automatically change the way they relate to the user or, in Tesla’s case, the way they interact with the context in which they find themselves.

Knowing how machine learning or machine learning algorithms work is essential to understanding how you can profit from them for your business.

Also Read : The 8 Benefits Of Cloud Computing For Your Business