Machine Learning is a part of Artificial Intelligence which enables the machines to automatically learn and also to improve the experience without having the need to be programmed explicitly.
Machine Learning helps the companies to derive more accurate data which allows them to take better decisions. Proper approach to Machine Learning also enables the organization’s to address the problems and errors that the early traditional approaches couldn’t. But we should also know that Machine Learning is not some sort of magic.
WHY DOES IT MATTER?
Why has machine learning become so important? It is because of the increased market of Artificial Intelligence. The main focus of machine learning is on teaching machines how to perform some of the human tasks that too on the basis of their past experiences. The machine learning approach to Artificial Intelligence is different from the classic approach to Artificial Intelligence. In Classical Machine Learning approach the machines are explicitly programmed step by step, so that they can follow the rules. In this there is no place for the performing of actions based on insights but in Machine Learning the classical style of learning is combined with the basic rules of knowledge. Also in this, the machines or the computers are allowed to grow on their own.
These features of Machine Learning have made it the most dominant subset of Artificial Intelligence practiced round the world.
THE TYPE OF MACHINE LEARNING:
You may wonder that how many types of machine learning are there or are there any divisions of Machine Learning at all. So let me make it clear that machine learning has further divisions and the best way to divide Machine Learning is on the basis of how the machine learns and henceforth we get the following types of Machine Learning –
- Supervised Learning – in this type of learning you get the desired output.
- Unsupervised learning – In Unsupervised learning the output data isn’t clear.
- Semi supervised Learning – In semi supervised learning only a few outputs are desired ones.
- Reinforcement learning – This is an ambitious approach to Machine Learning. That is in this approach the machine is rewarded on the basis of the results or outputs.
NEURAL NETWORK AND HOW THEY ARE TRAINED:
Neural networks are very important group of algorithms in both: supervised learning and unsupervised machine learning. The structure of neural networks is loosely inspired just like that of a brain. Also, the structure contains interconnected layers of algorithms known as neurons which serve to transfer data from one layer to other and also in this the output of the former layer forms the input of the subsequent layer.
WHAT ARE THE LANGUAGES USED BY THE MACHINE LEARNERS?
The machine Learner’s use different programming languages because Machine Learning is a huge field and it is very difficult to cover the whole field with only one programming language. Currently Python tops the list of machine learning languages. Other options for programming languages are – Java, C++ and R.
WHAT IS THE REASON BEHING THE SUCCESS OF MACHINE LEARNING?
Machine Learning is not new but the interest in machine learning has grown in the recent years. Probably, there can be two basic reasons which have resulted in the huge success of machine learning.
The first factor can be the easy access to the huge amount of pictures, text, videos, audios and information to the researchers who need it to train the machines.
The next and the most important point can be the availability of the vast amount of power processing GPU'S which can be used to form clusters to form machine learning power houses.
CAN MACHINE LEARNING BE THE PERFECT SOLUTION TO ALL ARTIFICIAL INTELLIGENCE PROBLEMS?
The answer to this question is not definite. Machine Learning is fallible and it can even be subject to the human biases. But, Machine Learning has definitely revolutionized the whole of Artificial Intelligence and has also made it available to the masses. So Machine Learning is a great tool for sure.
Effective use of machine learning helps to understand the basic concepts of broader analytics environment. Through this article you have learnt everything that is needed to be known in machine learning.