Machine learning : What is ML : What is machine learning

 

Machine learning : What is ML :  What is machine learning: Start applying it in your life

Have you always wanted to know what machine learning is but for one thing or another you could never fully understand it? Do not blame yourself! The truth is that it is a fairly complex concept and its implications in today's world evolve minute by minute.

In this note, we will tell you everything you need to know about what machine learning is, what its history is, and how it works, broadly speaking. In addition, we will recommend a machine learning course so that you can take your knowledge on the subject to a new project. 

The learning process of human beings is so complex that thinking that a computer can learn the way we can seem to be part of a science fiction movie. In this note, we will be as clear and concise as possible! So learning what machine learning is is not a headache. 

For example,  did you know that behind our Google searches, or Netflix suggestions for this weekend, there is a system that is learning from our online behavior? Let's see once and for all what machine learning is and how it impacts our day-to-day lives. 

What is Machine Learning or Automatic Learning?

Machine Learning is a type of artificial intelligence that, through algorithms, machines use statistics to find patterns in data and to be able to predict new values ​​and behaviors. 

These statistics allow applications to be more precise in predicting results, without being explicitly programmed to do so.

According to IBM, machine learning is not a simple process at all and requires high levels of programming to function properly. The key to that concept is that machines learn from data and not from a programmed command. 

Does the word algorithm sound familiar to you? It is very common to hear it in conversations on social networks. Both influencers and other Internet users are always browsing under the rules of the algorithm of the platform where they are. But what does this have to do with machine learning?

Below we will tell you how machine learning works and how it relates to this concept. Stay until the end and discover how machine learning affects us on a day-to-day basis!

If you want to immerse yourself in the world of programming and data, check out our Data and Analytics online courses and start to professionalize yourself. 

How does Machine Learning work?

Now that you know what machine learning is, let's see how it works.

According to Medium, machine learning is nothing more than a tagger of things and works as a technological classifier of the data that circulates through information systems. 

In this way, we can say that machine learning is to a computer what language is to the human brain. When you see this or that image on a screen or perhaps in real life, your brain encodes that information and translates it into a word or thought. This is how machine learning works!   

For example, when a photography application can differentiate between a dog and a cat. The first thing we have to do is show images of both dogs and cats so that the program finds patterns in each of the images. 

Through artificial intelligence, the system will find the differences between these two animals, and thus, in the future, it will be able to determine on its own which is a dog and which is a cat, without the intervention of a human being.

The role of data for machine learning

Of course, machines can fail, so the more information we load into the system, the better the application learning results. This is what we mean when we say that the machine learning algorithm feeds on data and not on programmed orders. If you are already passionate about the subject, you will be excited to know the different types of machine learning that exist!

In this way, we can say that machine learning works as a tagger or classifier of things that feed on the data itself. The more data, the more ability to label. At first glance, it looks like a science fiction story, but the reality is that it is nothing more than a database system that finds results based on similarity. 

The great leap that machine learning produces in the world of programming is that we no longer have to give step-by-step instructions to the computer, which are very difficult to create but must act by example. You can also apply machine learning in Python!

History of Machine Learning, where does it come from?

To talk about the history of machine learning, first, it is necessary that we develop a little the future of Artificial Intelligence in the world of technology. Well, machine learning is nothing without AI.

In 1952, Arthur Samuel created one of the first early learning machines, with the ability to play checkers. He used guides written down by expert players and played against himself to learn how to tell the right moves from the bad.

Just 4 years later, in 1956, the term Artificial Intelligence was born. Since then, other machines capable of Playing Backgammon were created in 1992, and in 1997 IBM created the first to be able to play chess. Wow, scientists are looking for someone to play with!  

The rest of the history of machine learning is just as you imagine it: more data, more learning. In this way, scientists were teaching more details to computers that, thanks to algorithms, managed to defeat human specialists in the subject. 

So much so that its application began to diversify and machine learning went from a harmless game of chess to its best-known applications such as the algorithm in social networks or digital content platforms.

Read on and find out how affected we are by this type of technology! 

Source: Pexels

How does Machine Learning impact today?

At present, artificial intelligence along with machine learning continues to grow day by day. Thanks to machine learning,  the recommendation systems used by Netflix, YouTube, and Spotify are currently working.

Through the content that you reproduce and the "I like" or "I am not interested", its system collects this data and compares it with that of other users. That way, it gives you more accurate suggestions that will make you continue to enjoy the service of these platforms.

Similarly, search engines like Google learn based on your search history. Social networks such as Facebook, Instagram, and Twitter, use machine learning to determine what to show you on the home page.

Do you remember those times when everything was in chronological order? It seems very far now. Social networks collect every reaction, comment, video seen, places visited and pages we like to offer us better experiences. Although some say that machine learning can be for a bit more obscure purposes, what do you think?

Source: Pexels

Industries and Machine Learning Today

At the beginning of the century, it was something very crazy to be able to have our own artificial intelligence assistants in our pockets or in our rooms. But just as you're thinking: that's right, Siri or Alexa are also experts in machine learning. 

In addition to communications, many industries are now using machine learning in their processes. For example, we find machine learning in climate control; the systems keep track of temperature changes to predict catastrophes like cyclones. And also in marketing, to be able to receive adequate publicity on the internet and recommendations for your next purchase on the internet.

In education, they are beginning to follow the concentration patterns of students and how to improve these rates. Would you like to create your own reports to show these results? Download our free template!

Did you want more? Check out the  11 uses of machine learning that you never imagined before.

Now, do you understand why every time you want to buy something it appears everywhere? Undoubtedly, a future awaits us where machine learning helps us speed up many processes and make our lives simpler. 

If you liked this topic and want to know more about it, do not hesitate to enroll in our online introductory course to Machine Learning, in which you will learn the basic concepts of Machine Learning and the opportunities and challenges of implementing it in organizations. I hope you understand better about this Machine learning : What is ML :  What is machine learning. 

Good luck and don't forget to train your algorithm in the best way!