What is Machine Learning? Why nowadays everyone talks about it? Can it help mankind solve complex problems?
All the above, are some questions that come to our minds when we hear the term “Machine Learning”. In one of previous articles, I explained what Data Science is. In this article, we will talk about Machine Learning, which is fully interconnected with Data Science.
Machine Learning has been Around for Years
Machine Learning is not something new, at least as a concept. It has been around for some decades. If you search in Wikipedia, you will find the following definition about Machine Learning: Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed.
If we tried to redefine Machine Learning with even simpler terms, we could say that it is that field of computer science based on which you develop a software application with an initial logic, and the application can learn new things itself and expand its logic autonomously.
Machine Learning’s Relation to Artificial Intelligence
Machine learning is considered a branch of Artificial Intelligence (AI). Artificial Intelligence is the broader concept of having machines carrying out tasks usually performed by humans and are considered “smart”.
Even though Artificial Intelligence and Machine Learning have been around for some decades now, they became hot buzzwords only in the last few years. The reason for this, is data. Not just data but Big Data. Big Data are extremely large sets of data that need to be analyzed in order to extract useful knowledge in the form of patterns, trends and associations. This computational process is described with the term “Data Mining“.
Big Data
Big Data is a concept that appeared in the last few years. Why? Because we now live in a “connected world”. We are always connected to the Internet and the social media. We produce and exchange vast amounts of information and different types of data all the time. There is data everywhere: data in the social media, data in enterprises, data in medical research, data in our smartphones, smart TVs, and the list goes on. All this data without being analyzed are just raw data. If analyzed, can be transformed to useful knowledge.
It would be very difficult for human beings to analyze Big Data and generate comprehensive knowledge, due to the large data volumes and complexity. Therefore, something else is needed for efficiently performing the transformation of data into knowledge and this is where Machine Learning comes.
So, let’s try to define one more time “Machine Learning” using what mentioned above: Machine Learning is that part of Artificial Intelligence which via Data Mining processes can analyze vast amounts of data (Big Data) and transform the data into knowledge by identifying patterns and trends. By doing that, Machine Learning applications can become “smarter” thus being able to educate themselves.
Applications of Data Science and Machine Learning
We can easily identify many applications of Machine Learning in our everyday life. Some examples are:
- Self-driving cars
- Speech recognition
- Personalized news feeds in social media platforms
- Data security (i.e. antivirus programs, anti-malware programs)
- Personalized marketing
- Online search
- Spam filters
As technology and computational power evolve, we will be witnessing even more spectacular uses and applications of Machine Learning and Artificial Intelligence. As it seems, Sci-Fi films are not so fictional anymore!
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Artemakis Artemiou, a distinguished Senior Database and Software Architect, brings over 20 years of expertise to the IT industry. A Certified Database, Cloud, and AI professional, he earned the Microsoft Data Platform MVP title for nine consecutive years (2009-2018). As the founder of SQLNetHub and GnoelixiAI Hub, Artemakis is dedicated to sharing his knowledge and democratizing education on various fields such as: Databases, Cloud, AI, and Software Development. His commitment to simplicity and knowledge sharing defines his impactful presence in the tech community.