Applications of Machine Learning: A Comprehensive Guide

We started off with computers that could do simple calculations. Then we moved on to more complex ones. Soon, computers overtook major aspects of our lives, and then came the pocket computer – the smartphone! And as we move forward now, we move on to more advanced technologies. Machine learning is one of them. We now have machines that can learn by themselves, providing more value than ever before. Read on to know more about machine learning and its applications!

Quick Summary

In this blog, we’ll be going through the various applications of machine learning along with knowing about what it is and why we need it.

What is Machine Learning?

Machine learning refers to the use of systems that learn and adapt without any direct instruction/guidance. These are programmed through the use of algorithms and statistical models that help in the analysis of data, helping draw key inferences from them.

Best Machine Learning Applications

Machine learning has evolved to become more and more integral in day-to-day life. Ever notice how the ‘auto-correct’ feature in your phone’s keyboard starts completing names? It ‘learned’ to do that by going through your contacts list. With the rise of AI, machine learning has been one of the most promising things that AI has brought with it. Let’s go through the various ML applications and know more about it!

1. Image Recognition

Have you seen how your photos/camera gallery can classify photos based on people’s faces? Yes, that’s image recognition. It’s the same with google lens. You add in a picture and it will search the web for you, finding images that are similar. Basically, it helps analyze and classify visual data in an accurate fashion.

2. Speech Recognition

Notice how saying ‘Hey Siri’ in your voice activates it, but not when someone else does the same? It recognizes your voice in a specific manner. That’s not all, they convert whatever you say into text – after which you get an answer/get your task done. This is where speech recognition is utilized through the use of ML.

3. Product recommendations

Say, you’re searching for a phone on Amazon. You pick the top-of-the-line iPhone, one that you’ve been saving for quite some time now. Just as you’re about to check out, you get a recommendation for a phone case and a tempered glass that you can pair with the phone. That’s where machine learning came into play. The algorithm sensed that you’re picking a phone, and suggested you accessories for the same. It’s one of the ways that machine learning empowers product recommendations.

4. Self-driving cars

We’ve all seen those sci-fi movies where you get cars that work without drivers. Just like the batmobile in the batman films, how it gets to Batman without anyone driving it. But now, we’ve got Teslas. Cars that can self-drive, and are actually good at it as well! It’s all because of machine learning, using which cars can judge their surroundings and can make decisions as well.

5. Online Fraud Detection

Machine learning works on patterns. Through advanced algorithms, it is able to identify anomalies if they occur. This helps in monitoring and detecting frauds. For example, suspicious activity can be flagged by ML, leading to the prevention of frauds through analyzing and identifying behaviour/habits of a consumer. For example, a person may be continuously changing their credentials, a classical situation wherein an individual tries to commit fraud. ML algorithms can easily pick that up, resulting in quick identification and preventing frauds from happening.

6. Medical Diagnosis

One of the major fields wherein machine learning has made a mark is undoubtedly healthcare. In the medical field, machine learning helps diagnose conditions with a high rate of accuracy. For example, an algorithm can help you determine if a patient has a tumour on their lung as you feed the system with data like x-rays, MRIs and more. It will use its understanding and existing data that it has been fed to diagnose and determine what type of disease a person has.

7. Automatic Language Translation

Ever noticed how you can highlight any text using Google Lens and it provides you with a translation in a couple of clicks?
Or when you can directly speak into Google Translate and it can detect as well as translate for you? That’s possible through machine learning. It uses its language depository that’s paired with machine learning algorithms to get you accurate translations, breaking barriers all over.

8. Banking Domain

With cybercrime reaching all-time highs, banks need to level-up things. This means getting stricter measures to prevent any type of fraud. And this is exactly where machine learning shines. It helps protect accounts from hackers and fraudulent entities.
With a filter, these ML models help banks and other financial institutions stay safe.

9. Stock Market Trading

The stock market is volatile in nature. Still, it does have a tendency to work on patterns. And that’s exactly what ML is all about. With algorithms and in-depth data analyzing capabilities, these systems give accurate market forecasts based on trends.
Though ML one can become a better stock market trader – only if it is used in the correct manner.

10. Automating Employee Access Control

There are various departments that constitute an organization. There’s marketing, operations, HR, sales and many more. But, how can one determine how much access an employee actually requires? That’s where ML shows its magic. Once you feed the necessary data into an ML model, it can determine the amount of access that an employee requires

11. Regulating Healthcare Efficiency and Medical Services

Efficient healthcare regulation ensures that medical services are accessible, cost-effective, and high-quality. By implementing standardized protocols, healthcare providers can reduce medical errors, streamline patient care, and optimize resource allocation. Proper regulations also help in controlling healthcare costs, ensuring fair pricing, and maintaining ethical medical practices. With advancements in technology and AI-driven solutions, healthcare systems can enhance efficiency while complying with regulatory standards to improve patient outcomes.

12. Marine Wildlife Preservation

Machine learning algorithms can be used to preserve marine life as well.
Yes, you heard that right! Behaviour models can be developed using ML algorithms, helping scientists in regulating the populations of sea dwellers. These models also help in monitoring endangered as well as at risk species, providing you with a balanced preservation effort.

Also Read: One of the Best Python Libraries for Machine Learning

Why do we need Machine Learning?

As part of the AI revolution, ML represents an integral part of the same. AI is way, way smarter when it is paired with ML. The ability to learn is perhaps the defining aspect of AI – making it more human than ever. And with the many applications, ML gives AI models the ability to learn from patterns. Let’s take a look at the value that ML brings with it:

1. Handling Large Volumes of Data

The biggest dilemma with data is that its scale is unpredictable. It can be less than a megabyte or can go more than a million terabytes. This disparity of scale also requires a disparity in the resources required to analyze this data. Because analyzing a million terabytes by a human is simply impossible. That’s where ML models take the lead, getting your data analysis to new heights.

2. Solving Complex Business Problems

You need a little more than just some lines of code to solve business problems. One needs to go above and beyond not only in the form of statistics, but in also forecasting the impact that a decision might have. And that’s where ML models shine. They’ll help you with statistical as well as overall decision-making efforts, helping you solve problems effectively and easily.

3. Automate Repetitive Tasks

Machine learning streamlines workflows by automating repetitive and time-consuming tasks. Automation gets you increased efficiency by freeing up human resources, letting them focus more on core issues rather than repetitive ones.

4. Self-Improvement in Performance

Unlike traditional programs that require manual updates, machine learning models improve themselves over time by learning from new data. This continuous enhancement gives you better accuracy and efficiency.

5. Personalized User Experience

Machine learning powers recommendation engines, targeted marketing, and adaptive learning systems. Platforms like Netflix, Spotify, and e-commerce sites use it to provide super-customized content and suggestions. All this leads to an elevated user experience.

Conclusion

Well, that’s pretty much it!

We started off with what ML is, moving on towards ML applications and going over its use cases. ML is one of AI’s prime offerings, and its advantages are simply too many to count!

The ability to learn is AI’s #1 advantage. And for us humans, it then becomes our #1 advantage. Do you require ML models that are fine-tuned to your business and ones that get you your desired results?

RejoiceHUB LLP gets you exactly that! Let’s connect and create together!