APPLICATIONS OF MACHINE LEARNING IN REAL WORLD

Applications of
Machine Learning In Real World.

Machine learning is one modern innovation that has helped man enhance many industrial and professional processes and advance everyday living.

Currently, machine learning has been used in multiple fields and industries. For example, medical diagnosis, image processing, prediction, classification, learning association, regression, etc.

Intelligent systems built on machine learning algorithms have the capability to learn from past experience or historical data. Machine learning applications provide results on the basis of past experience.

Applications of Machine Learning In Real World. Thingscouplesdo.com

Machine learning is one of the top-notch technologies of the digital era. It has sped up the computation processes to achieve quality results in minimal time.

It has positively impacted the industries, financial and medical sectors, and our daily lives.

This blog will discuss the applications of machine learning in real world. It’s essential to define and discuss the concept of machine learning to understand the applications of machine learning in real-world better.

What Is Machine Learning?

Machine learning is a sub-branch of AI (Artificial Intelligence) that deals with data statistics. It helps us to build and use modern computers for analyzing the existing databases. It lets businesses predict human behaviors on a particular timescale by analyzing the available data.

Top 5 Applications of Machine Learning In Real World

Machine learning plays a vital role for many businesses in designing proactive business models. It analyzes the data better than we humans can do. There is a continuously growing list of industries and businesses adopting machine learning. We have compiled a list of top applications of machine learning in real world below;

1) Image Recognition

It is one of the most common uses of machine learning in real world. Its complex algorithms take every object as an image and have the capacity to distinguish these images by analyzing the intensity of pixels. Let’s have a look at machine learning’s image-recognition use cases in the real world;
• Images tagging on social media
• Analyze X-rays to detect cancer
• Used to differentiate handwritten and computerized writing
• Law enforcement agencies use machine learning facial recognition features to identify a person by analyzing a database of images.

Machine learning makes all the above-listed real world applications by differentiating the images based on pixels’ intensity.

2) Speech Recognition

Machine learning translates the voice signals into the text by analyzing the frequency and
magnitude of the voice signals. This concept is known as speech recognition or automatic speech recognition (ASR).

Today, nearly all the artificial intelligence-based automating appliances use speech recognition facilities.

We have compiled a list of speech recognition use cases in real world below;
• Google Voice Search, Alexa, and Siri
• Electronic appliance control
• IoT equipped appliances

3) Medical Sector

Machine learning is doing wonders in the medical sector by helping physicians predict and diagnose diseases.

Let’s have a look at some of its real-world use cases in the medical sector;
• Machine learning advanced analyzing algorithms assists docs in diagnosing the disease.
And most of the time, it helps medics to predict the disease during the incubation period.
• It helps the pathology departs to analyze the body fluids on behalf of fed permeates.
• Machine learning is widely used in Oncology depart to help docs diagnose cancer and
recommend suitable medicines.
• It assists docs in diagnosing genetic diseases by analyzing the patients’ photos and medical history over a particular period.

5) Financial Sector

Machine learning is one of the potential forces behind the popularity of Fintech. It is helping the banks and financial sectors to make intelligent decisions and stick to the proactive business model.

Let’s have a look at machine learning real-world use cases in the financial sector below;
• Credit Scoring – Machine learning analyzes a person or company’s bank records to assign a credit score. This credit score helps banks and other financial institutions to mitigate lending risks.
• Fraud detection – Hacking, theft, and fraudulent activities are common problems in the banking and financial sectors throughout the world.

In 2020, UK financial sector alone had lost 159.7 million British pounds because of online banking frauds. Machine learning algorithms can help financial institutions outsmart the hackers and fraudulent activities by timely recognizing the unusual activities. ML can detect fraudulent activities at the initial stages and trigger the defined mitigation protocol without human interaction.

Also in Stock Market, – Machine learning lays the foundation of our financial future. It can analyze the number of data sources in real-time to draw a behavioral pattern of the market over a time scale.

It can compare the data of several decades in a few seconds to bring out the statistical data on defined parameters.

Machine learning is an incredible gift for the financial sector. It is helping nearly all businesses to make intelligent decisions, avoid scams, and draw an ideal business and marketing strategy.

5) Predictive Analysis

It is a predictive analysis feature that makes machine learning an incredible technology.

Machine learning can amazingly classify the bulk databases with exabytes of data. After classifying data, it can perform predictive analysis on a defined set of rules.

Predictive analysis is one of the widely used machine learning examples. We have compiled a list of its real-world use cases below;
• It helps the financial institutions to differentiate the legitimate and fraudulent transactions.
• It helps businesses to predict a potential market behavior towards a product/service over a particular timescale.
• It helps banks to predict the credit score of a loan applicant.

Final Words | Applications of Machine Learning in Real World

Machine learning is a blend of data science and AI technologies. It is helping a wide range of businesses to design proactive business and marketing approaches by analyzing data on defined parameters.

We have discussed applications of machine learning in real world from medical to financial sectors.

SEE ALSO :  TOP 10 BUSINESS BENEFITS OF MACHINE LEARNING

Machine learning is doing wonders for businesses of all sizes. You may incorporate machine learning into your business to keep your business ahead of its competitors.

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