As we know that technologies are making a boom in day to day life in which Machine Learning is one of the booming technology that helps the user to make their life easy and comfortable.
It is a particular type of technology that enables the machine to acquire or give a prediction on the basis of past data. Plenty of definitions are available for Machine Learning, one of them is given by Arthur Samuel in 1959.
He defined “Machine Learning as the area of study that allows computers the capability to read and understand itself without being programmed or instructed explicitly”.
In simple language, you can say that machine learning draws together statistics and computer science, empowers computers to study and agree how to implement a given task without being instructed, same as our brain used to improve the task so as the computers also use their knowledge and experiences to do all the work.
For example, how computers are being able to tell the separation between the picture from a dog and the picture of a cat, you can begin by feeding the images to computer and telling it that this is a dog and that one is a cat, then only the computers are being able to recognize the difference between a dog and a cat.
Machine Learning plays a very important role in our day to day life, But how?(Read here). You can take the example of your phone or google, nowadays when you want to search anything on google you only have to give him the instructions, only Google will do the same as you want only by listening, you don’t have to type anymore like the earlier days.
Same as you speak to your phone with the help of Google Assistance, whatever you say to your phone for calls, messages, etc. you just have to say it and the work is done.
Google Assistant: an application of machine learning
(As the term recommendation came into play, pick up its basic through this blog)
For example, ML algorithms designed for the evaluation of loan application, credit card defaulters, medical diagnosis application, etc.
Machine learning also brings clearness in decision making in multiple domains like HR treats candidates equally without considering other factors such as age, gender, religion, caste, race, etc. It shows transparency in the rules and regulations of an organization. (Of course, you will acquire more notion when read “What is HR Analytics? Role, Challenges and Applications”)
Machine Learning is also responsible for improving IT services, as companies generate a massive amount of data through hardware components, software components, server operators, etc. (Related blog: Exploratory Data Analysis before building ML models?).
Machine Learning models are employed to achieve, precise dataset, and present business insights in order to create the IT industry more proactive and hence improve their efficiency rapidly.
Nowadays the usage of robots increases day by day. In Chennai, the restaurant named “Eatery” has robot waiters who serve customers, speak to them in Tamil and English.
They have a team of seven robots designed in blue and white. Each robot in the Eatery costs around Rs 5 lakh. The hotel staff of the Eatery will be able to teach all the robots from their life experiences; this is the live example of Machine Learning where the person will be able to teach the machines from their knowledge and experience.
Robotic Services in a restaurant: robots in place of waiters
Just like Chennai many other states and countries also have these types of restaurants and hotels such as Kerala, China, Boston, etc. where the robotic waiters and other staff used to do all the work on their own only with the help of little guidance, knowledge, and experience. This is the biggest example of Machine Learning where the machine tries to learn how to behave and work like humans.
Robotic deployment has a significant role in health, finance, and banking, even in the manufacturing industry where robots make the work much easier. There is a human to operate robots and a creative human brain inventing their plan or blueprint.
Nowadays developers used to develop more advanced and latest applications for the users like the facial-recognition, speech-recognition, vision-recognition, and thumb impression in their applications to make it more reliable and safe applications.
In finance, new technologies take a position such as a blockchain that has collided with India’s Capital Markets. For example, Capital Market users use this application blockchain to detect fraud and also to predict the movements in the market. This is how our finance market also takes ML help to do their work. (Related blog: Do Blockchain and Artificial Intelligence Incorporate an Ideal Model?)
In the real estate business, ML also takes part with the help of an advanced CRM system named Contactually, specially developed or designed to connect WA DC-based investors and startups.
The additional power of Machine Learning (ML) algorithms changes the static system into a live interactive machine that answers, approves, and nominates. This is the place where Machine Learning takes part very effectively and helps a lot to make our future better with the help of advanced technologies.
As the ML algorithms manipulate data generated by several servers, there is also an equal chance of hacking the same data as multiple devices are connected to the internet.
So Machine learning works in both ways if it is used by data hackers can result in strong attack whereas it can be implemented by cybersecurity firms in order to increase the security level. (Have a glance at the blog: Cybersecurity in the IoT world).
We have studied all the benefits of Machine Learning with their future and upcoming advancements. Along with that, also it will help you a lot in dealing with your day to day life with lots of new real-world applications.
Machine Learning is having a very bright future because of the type of advancement and development we have nowadays in our applications due to which we make our life more easy-going and appropriate.
Machine Learning is less time consuming and also energy saving which will give you a meaningful life. For more blogs in Analytics and new technologies do read Analytics Steps.
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