Significance & Real Life Applications of Machine Learning

We all agree that progressively machine learning has played a pivotal role in improving business operations and automating routine tasks thus making human life easier.

Within the blink of an eye machine learning systems can recognize patterns and relationships in data to help in face recognition, voice recognition, object detection, and powering a driverless car. Let’s dive into what is machine learning algorithm and the applications of machine learning.

In simple language, it means these algorithms are a set of rules or processes used by an AI machine to evaluate, recognize, or discover new insights or patterns and relationships in data and then predict the output values once data is fed to it.

Significance of Machine Learning

Do you know why machine learning is important? Ml algorithms are programmed to analyse huge amounts of data and find its hidden patterns and correlations that otherwise are not possible for humans to detect. This has been possible due to their access to:

• Real-Time Information: 

This application helps to give the details about the latest happening in the market. Machine Learning algorithms use the real-time information to find hidden data trends and feed us the proper market information.

• Stock Prediction:

Stock Price Prediction using machine learning is the process of predicting the future value of a stock traded on a stock exchange for reaping profits. With multiple factors involved in predicting stock prices, it is challenging to predict stock prices with high accuracy, and this is where machine learning plays a vital role.

• Security:

The software for machine learning systems is programmed in a manner to:

• Predict fraudulent activities that make it secure for users.
• Detect cyber threats by monitoring constantly the system for any suspicious activities.
• Process numerous data amounts in real time to look out for any critical incidents.
• Detect any new malicious files or malware.  
• Protects data in cloud apps and platforms.
• Detects malware even in encrypted networks. 

Real Life Applications of Machine Learning

1.User Pattern Recognition

Ever wondered when we use apps like Spotify, or Netflix, we always get to see suggestions that they offer to the use based on our viewing or listening history? Many e-commerce websites like Amazon are using machine learning models to predict user preferences. This feature enables the website to track the behaviour of the visitor from his/her previous purchases and shopping cart history.

2. Social Media Data Connection

“People You May Know”, is a feature on Social media platforms like Facebook, Instagram, LinkedIn, X(earlier known as Twitter)  that you often get to see. It also works on a machine learning algorithm that takes data from your comments, contacts, likes, and existing connections from your real-life friends list and prompts you to connect with them.

3. Image Recognition by Machines

This type of algorithm is designed to identify the images of the objects that we have programmed into them. It allows the machine to only recognize whether the objects present in a set of images belong to it or another one. For a machine, an image is just data comprising of array of pixel values. This is used in facial recognition that we use in our daily lives. Password protection methods like Face ID are commonly used by police, detectives, spies, and investigators to help them nab the culprits.

4. Use in the Healthcare Industry

There are numerous examples of the use of machine learning in healthcare systems. Some are

• Drug discovery
• Personalized treatment
• Dermatology assessments
• Use in therapeutics
• Medical recordkeeping
• Medical imaging
• Robotics surgery

One of the greatest uses of machine learning is in the healthcare industry. It’s possible only by using wearable devices such as wearable fitness trackers and smart health watches, etc. Such devices are used to monitor the users’ health data in real time.

ML algorithms help medical experts to predict the lifespan of a patient who suffers from any chronic disease with accuracy. Robotic surgery is one of the examples of machine learning in the healthcare industry.

Robotic surgery is of great value in the healthcare industry as the robots are programmed in a manner that they can conduct surgical procedures with utmost precision, accuracy, and flexibility better than a surgeon.

5. Use in the Automation Industry (Self Driving cars)

After healthcare industry, the automotive industry is one of the areas where there is machine learning has made significant strides with the help of image and speech recognition. Machine learning algorithms

• Analyse images and speech data to recognize patterns.
• Thus, it becomes easy for it to identify objects, people, and emotions accurately. Take for example, self-driving cars use machine learning algorithms to recognize road signs and identify objects on the road.
• Major companies like Tesla, Mercedes Benz, and Nissan have made a huge investment in machine learning novel innovations.

Scope of Machine Learning

• We read a lot about the scope of Machine learning, ML jobs and applications have a vast scope, and it is used in many different fields.
• The major scope of machine learning is data analysis. It takes automatic insights from data that can help you drive business value. It has major scope in healthcare, retail, agriculture, finance, and many others.
• Every day its scope is increasing drastically as many small to medium businesses want to adopt this technology to improve their customer service and overall productivity and efficiency.

Conclusion

Overall, machine learning is a hyped technological tool that can help businesses automate tasks, detect data to make better decisions, and learn from data to improve their operations. With the availability of the right data and with careful data manipulation and considering the underlying limitations, machine learning can truly be an asset for any business. In future years we can foresee there is brisk demand for machine learning technology.