The scope of machine learning has increased considerably since the volume of data has increased. Machine learning algorithms are used for both optimization as well as automation of various processes in the present time.
Machine learning finds application in many fields like medical diagnosis, e-commerce, analytics, banking and finance, social media monitoring, smart assistants, and the like. Overall, the number of domains that utilize various techniques of machine learning may increase further in the future. This calls for preparation in the form of courses and skills that are exclusively dedicated to machine learning. In the future, a certificate in machine learning could act as a virtual passport for the job market.
The traditional sectors that are least influenced by machine learning are also leveraging the power of machine learning in various departments to benefit from this emerging technology. Let’s take a look at some of the most important domains where machine learning is playing a pivotal role.
Transportation: Navigating with intelligent systems
In order to travel from one place to another, various options of means of transportation are available. With the help of systems that are powered by machine learning, we can choose the best option available to us. For instance, Google Maps makes use of location data and synchronizes it with traffic congestion, site location, and alternative routes.
With the help of this information, commutation time can be predicted and the fastest route to travel from one place to another can be taken.
It needs to be noted at this point in time that machine learning algorithms also find usage in applications that coordinate cab facilities in metropolitan cities. This is true for flourishing businesses like Uber and Ola.
Machine learning systems help in the estimation of the price of a cab ride as well as pickup and drop location. They also help in choosing the shortest route to a destination thereby facilitating smooth and quick journeys.
Machine learning has numerous applications in emails like classification, spam filtering, and sending automatic replies. With the help of machine learning techniques, we can classify an email as spam. Though there are other ways to classify an email as spam, machine learning methodology is very accurate.
In addition to this, machine learning techniques are also useful for classifying emails into different types like primary, promotions, and social. Machine learning techniques also prove helpful in sending smart replies during a time when we may not be attending our mailbox.
In the financial domain like finance, it helps in the detection of fraud and makes transactions very safe and secure.
In the present time, the banking system has become fully automated. So, the role of machine learning has increased accordingly. Machine learning is now playing a role in portfolio management in the financial sector. It is also handy in algorithmic trading and affiliated applications in the stock market.
With the help of machine learning, we can predict the fluctuations in the stock market and invest in the most stable assets and shares. High-frequency trading is also possible with the help of machine learning applications.
The automated approval of loans as well as their risk management is also made easier by deploying systems powered by machine learning.
Needless to mention, machine learning helps in the analysis of a large number of financial documents in a short span of time, thereby, improving our analytical capabilities.
In the medical sector, machine learning is being applied to detect various irregularities in medical data. It also helps in the analysis of various scans and medical reports in a precise manner. It helps in the monitoring of patients and keeps track of their medical reports over a period of time. This helps in effective diagnosis as well as treatment of ailments in a timely manner.
Robotic surgeries, telemedicine, and drug discovery are some of the other areas where machine learning has a pivotal role to play.
The way ahead
The number of sectors where machine learning finds application is constantly increasing. Consequently, the processes, systems, and algorithms of machine learning are undergoing advancements in a holistic way.
Ranging from optimization of business operations to predicting the pulse of the market, machine learning is finding applications in newer sectors in one way or the other.