Evolution of technology and the precious gift of Machine learning has amplified the potential of growth and opportunity to an altogether incomparable standards.
Know About Machine Learning
In this article, we are going to talk right from the beginning. Here we will discuss briefly from where machine learning originated, we will talk about machine learning meaning, about the basics of machine learning. Let us go to the most primitive concepts. Before knowing about machine learning which is a subset of artificial intelligence, first learn about artificial intelligence.
What comes to your mind, when we talk about artificial intelligence? One might imagine virtual reality paving its way in the natural physical environment. You might be imagining a movie scene of Avengers where robots seems to be performing the tasks of humans, talking like humans and even doing stuff which is beyond human capacity. Or some might begin to imagine a way of life where the artificial intelligent machines lives in harmony with humans forming an alliance to make things easier and better for human living.
Performing things like feeding the kids, washing clothes, washing the cars, taking the dogs for a walk, carrying out the cleaning work in the medical clinic giving the medicine to the patients according to the prescription written on the paper and in the manufacturing plant carrying out the various tasks of production like packaging, storage, etc. or performing the task of security guard and many more useful advantages.
Some may have pessimistic view of artificial intelligence like robots overpowering humans and becoming more and more powerful with time. They seem to be snatching away the jobs of millions. They might be considered as a threat to humanity. All these are probable circumstances that may come to one’s imagination. But the reality is far from this moment’s dwelling.
In the global technological fraternity, the scientific engagement is not about Artificial Intelligence and the machine learning basics overpowering humans but it is about the building up of artificially intelligent machines. Scientists are working towards making this technology possible. Artificial technology and machine learning basics is about enabling computer programmed machines to work, think and behave like humans by applying their cognitive technological skills and creativity.
The technology is fast moving toward creation of such reality. Today, taking about machine learning and Artificial Intelligence, it has reached such magnanimous heights that it becomes important to know about this. It is the need of the present times. Many businesses have timely adopted artificial intelligence by the way of adopting about machine learning because they have realized how much advantageous and valuable it is, in the times to come.
It is becoming gradually evident that those businesses who don’t adopt this technology is doomed to lack behind in the times to come. Let us know what is Artificial Intelligence. John McCarthy is the trailblazer of Artificial Intelligence. The term AI is coined by him. Artificial intelligence aims towards achievement of artificially intelligent machines that have skills similar to humans that is reasoning, logical and problem solving.
They are fed upon tons of data and on the basis of data, logic and past experiences, they are acted. For a machine to be considered Artificially Intelligent, there are certain parameters that needs to be passed that is similar to human brain functioning, thought process, cognitive skills, rational behavior, etc.
When we talk about artificial intelligence and machine learning, we are not talking about futuristic application. It is about the present, there are so many things that we are using on a regular basis but we are not conscious about it. Are you an iPhone user? If yes, you must be using Siri, right.
What do you think actually is Siri? Siri is your personal virtual assistant. It is an example of artificial intelligence and machine learning. In apple phone, the Apple Music app is another artificial intelligence related thing that you are using.
The application is capable of presenting you a personalized preferable music options based on your previously listened music. Let’s take another example, you may have used Google Doc. Let me tell you briefly who doesn’t know what it is.
Google Doc application is a word processor where you can create, edit and store your files. Here, there are two ways by which you can type your text. One is typing on the keyboard area and another is audio recorder or speech recognition or automated recognition. As you speak, it automatically gets typed, that is, the audio is converted into text. This is one of the applications of Artificial intelligence and about machine learning usage that we are using on a daily basis.
Now, that you have a broader image of artificial intelligence. Let’s come to the basics of machine learning.
Machine learning is a term that was coined by Arthur Samuel. Tom Mitchell said about machine learning as “a computer program is said to learn from experience E with respect to some task T and some performance measure P, if it’s performance on T as measured by P, improves with experience E”. Machine learning in artificial intelligence involving bestowing the machine or computer program the ability to learn through the mode of training by feeding upon the information and on that basis it makes calculated and reasoned accurate end results.
Different type of machine learning
1. Supervised learning
As the name suggests, supervised learning involves the presence of supervisor. Just like in an enterprise, the supervisor guides, instructs to carry out a desired result under its supervision in the same manner, supervised learning involves the learning process by the way of training the machine by feeding the machine with the data which is properly labelled so that the machine analysis the previously held data and produces the correct outcome when it get exposed to new data.
2. Unsupervised learning
It is not provided training, it categorizes the unsorted things on the basis of similarities and differences.
3. Semi- supervised learning
Semi- supervised learning falls between the supervised learning and unsupervised learning. It has both labelled and unlabeled data. The algorithm learns from the combination of both the data.
4. Reinforcement learning
Reinforcement learning involves learning by performing action. It gives wider scope to machine and the agent to automatically figure out the ideal mode of action in relation to specific context to maximize the reward points.
5. Use of machine learning
In banking, finance and insurance, it helps in segmenting a group of customers and on that basis it is decided upon which offer is to be presented to whom. You must have received calls from different banks for different offers so what do you think, do they call everyone. No, it is not that. They call on the basis of what their calculated data predicts.
6. Social media platforms
You may have an account on Instagram. On your feeds, you gets the notice the posts of your friends and pages you like. Also in the extreme left there is a search option, which shows a variety of post right from music videos, dance videos, some poetry pages, news content, fashion blogs, movie clips, etc. What do you say about that, do they just show up of their own? No, they are actually based on your previously watched stuffs. Same goes for Netflix, where you are displayed with an option saying you may also like and below that you are given multiple choices. The option that they display is based on your previously watched movies. This is one way in which machine learning works.
In the healthcare sector, its application is of greater use and of utmost importance. It is used in the diagnosis of diseases, then it has its application in tracking down of the patient’s improvement, and in the planning of future course of treatment.
Essential Components of machine learning basic
There is no stativity involved in the machine learning algorithm, there are hundreds of new machine learning algorithm that comes up every now and then. Though every machine learning algorithm is different but some things remains essential and foundational to the making of the machine learning algorithm.
It’s just like a cake, which has inner structural material that remains the same in the making of all the cakes while the outer structure could be anything. In the same manner, there are three components of machine learning basics that are:
a) Representation: this means how the data or information is represented. This involves basic set of rules, neural networking, graph model, decision tree and many more.
b) Evaluation: This component involve evaluating the programming by the ways of possibility, predictions, trial and error method to narrow down the errors, correcting those errors in bringing about accuracy and efficiency.
c) Optimization: this involves constrained optimization, convex optimization, combinatorial optimization.
The innate capabilities and the advantages that the machines which are artificially intelligent have in giving highly efficient and accurate end results makes it all the more important with the present day demand and requirement for technological advancements and innovations in generation of technologies and concepts that are fruitful enough to make business environment easier and better.
It is to our advantage that we welcome such technological achievements and use it to our benefits rather than just holding back and being skeptical about the turn of events.