All You Need to Know about Machine Learning- Its Use Cases, Industries and Beyond

Machine learning is a big name in the tech arena, but it gets thrown around as a synonym for AI (Artificial Intelligence). It is a part of AI, but both are entirely different from each other.

For example, if we have to differentiate AI and ML broadly, we can say that AI is a broader concept that creates machines with human-like thinking capacity. At the same time, Machine Learning is an app with large amounts of data, enabling devices to learn from the data and act accordingly —that too without being programmed explicitly.

So, people are living around a lot of hype created around Machine Learning. What does this ML mean in the context of enterprise software? How does it work, and what value is it adding to today’s business? Most importantly, how will it evolve, and what should we expect from it in the future? There are so many questions that people want answers to. So, this article brings solutions to all questions that may have been explored for a long time. So, let explore;

What is Machine Learning

We have precisely explained Machine Learning earlier in this article. Still, if we talk about the straightforward definition of Machine Learning, then Azure says, “It’s the science of teaching or training machines to extract, learn, analyze and act, just like a human does.

How Machine Learning Evolved?

Even though Machine Learning came into the limelight recently, the term ML was coined and formulated back in the late 1950s. You might have heard Arthur L. Samuel, who created the first-ever Machine Learning application for IBM that played chess. However, in 1990, Machine Learning became the talk of the town. It was the period when the availability of the internet and the availability of usable data increased.

Did you know a McKinsey report stated that AI solutions are all set to deliver a whopping $13 trillion by 2030, contributing 1.2% of global GDP a year?

So, one thing is clear that machine learning enables machines to learn and act from the data. It is not just one, two, three, or hundred; it requires tens of thousands of data or even millions to train a machine.

Kind of Machine Learning

How does machine learning work? You must have this question in mind if you are coming across this ML term for the first time or not from the tech background. Well, to understand how machine learning works, you need to understand the kind of machine learning.

Did you know there are many ways through which a Machine learns?

And that categorizes Machine Learning into three kinds;

  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning

Supervised Learning: When you train a machine with labeled data or train a machine systematically, it is called Supervised Learning. For example, you gave machines lots of data with explanations, like Machine Learning Solutions in healthcare. You give plenty of labels to devices with clear instructions. Now, the machine will do as instructed. That means the machine has created a set of rules based on the data and works accordingly.

Unsupervised Learning: Suppose you have a large amount of data and you want to segregate those data into different clusters. Now, you feed a machine with the characteristics of the data, or you program a machine learning app with the characteristics. Now, the machine will learn and train itself and cluster all data accordingly. In simple terms, machines learn from the data and give you insights.

Reinforcement Learning: When a machine learns with the environment and feedback it receives is known as Reinforcement learning. For example, when you show the machine an image of a dog and ask it to recognize it and the machine recognizes it as a cat. Now, you give feedback saying, no, it’s not a dog, it’s a cat. Now, machines will learn from your feedback and act accordingly.

Benefits of Machine Learning

Machine Learning is a boon for the tech-savvy generation. An ML app can be powerful to revolutionize the way we do things and interact with them. It improves lifestyle, makes our job easy, and helps businesses grow. Let’s explore some of the top benefits of Machine Learning in detail. 

1. Identifies Trends and Patterns

Businesses use Machine Learning apps to empower AI machines, enabling them to discover specific trends and patterns. It can discover market trends and market best practices to help businesses create marketing strategies. Or, it can discover customers buying trends and patterns to help companies to increase sales. For instance, a fintech sector can help its customers invest safely by predicting the market much in advance. In contrast, an eCommerce site can provide more customized services to its customers after understanding their browsing behaviors and purchase histories. Amazon does it, and the result is before you —it’s the single largest eCommerce platform worldwide in terms of revenue.

2. ML App Enable Machine Functions without Human Intervention

Since Machine Learning has the ability to learn through data, it can automate tasks and do various activities without any human support. And, you know you don’t need to program the task. It can do it automatically. Automation means fully automation, not even programming required. ML-powered machines make predictions, learn from data and feedback it receives and improve its algorithms on their own.

3. Continues to Grow

Machine Learning learns through data. We have mentioned it earlier. As it gains experience, ML continues to improve its algorithms as it matures. That means;

More the Data > Better Model the Model > Higher will be the Accuracy.

For example, you need to make Machine Learning apps for healthcare. Now, the machine, at its initial stage, will provide limited support or based on the amount of data you have fed. Gradually, as it continues to receive patients’ health data and feedback, the machine’s algorithms will continue to evolve, coming up with more accurate predictions and higher efficiency.

4. Can Handle Unstructured and Multi-Dimensional Data

What happens when you have a large volume of unstructured data? No matter how important the data is, it is of no use for you if it is not appropriately structured. Machine learning helps you handle the data systematically. You will receive structured data with the help of a machine learning app. However, developing an ML app requires a partner with a reputed mobile app development company. 

5. There is an ML App for Every Business Niche

Whether you are running a brick-and-mortar shop or a large enterprise, Machine Learning has something exceptional to offer. Machine Learning apps have all the potential to take your business to a new height by helping you deliver personalized experiences to your customers and target the right customers.

Machine Learning Use Cases

Machine Learning can be used for various purposes, including external (client-facing) and internal business processes.

According to Statista, 58% of businesses, especially fintech sectors that use Artificial Intelligence, are using the Artificial Intelligence and Machine Learning Solution for fraud detection.

So, it can have various use cases for external and internal purposes. It can be used as customer services, voice assistants, product recommendation, pricing forecasts, team productivity, process improvements, and automation. We have built various AI/ML solutions for our clients. We have recently created one for our client MedTech that enables surgeons to assess patient risk better and implement appropriate treatment plans. You can explore the AI/ML Case Study here. Now, let us help you with various other use cases of ML in multiple fields.

1. Voice Assistants Powered by AI/ML

You must have Google Voice Assistants by saying “Ok Google” or “Hey Google” and Siri by saying “Hey Siri,” mustn’t you?

AI voice assistants have revolutionized the customer sector. Just a command can get you things you want. These voice assistants use machine learning algorithms to understand what you say, analyze what you want, and assist you with accurate results.

The use of voice assistants is not just limited to individuals; it can also be used for internal processes. For instance, doctors or surgeons in OR rooms can take the help of AI voice assistants for better treatments, patient care, and more. Similarly, voice assistants can be used for various other industries like retail, manufacturing, eCommerce, real estate, etc. They can deploy AI/ML chatbot to assist customers with their grievances.

2. Customer Service Automation

According to Semrush, 48% of companies use data analysis, machine learning, or AI tools to enhance data quality issues. In comparison, 80% of retail executives have expressed their desire to integrate and adopt AI-powered intelligent automation by 2027.  

Managing customers is one of the main breaking points for businesses today, especially those online. No doubt, it requires extensive human resources to manage the requirement. Whereas today’s customers want quicker results or else, they have plenty of options to explore. Speed, comfort, and convenience are the most favored choice for today’s tech-savvy generation. You need to provide or lose the customers. Machine learning apps can help you solve this issue by allowing you to integrate tools across all customers’ facing channels; one such example is AI chatbots which are powered by Machine Learning that gives machines learning, interpreting, and analyzing capabilities.

3. Cybersecurity

Everything online is vulnerable to hacking. You cannot stop it but can prevent it. It just needs attentiveness and how actively you respond to unwanted threats. With machine learning advanced algorithms, it has become easy to predict, identify, and mitigate threats quickly —thanks to predictive analytics. Machine Learning tools help businesses track users’ behavior (especially in the finance sector), spot irregularities, and find gaps in existing security protection shields.

4. Fraud Detection

We have mentioned that around 58% of businesses with AI/ML solutions use the technology for fraud detection. Obviously, financial transactions have increased more than ever as most people use mobile and net banking for faster services. It has given facilities to the costumes but has increased online fraud. Credit card companies and banks have deployed machine learning algorithms that precisely review each transaction carried out by customers. It understands their buying behavior, and hence it becomes easy for them to catch the irregularities.

5. Help Communicate Better

Mistakes and misunderstandings are expected today, and every human being commits this. But, in business, it can lead to some severe loss. For example, a single mistake in email correspondence, customer reviews, video conferencing can change the scenarios. Hence, machine learning tools can help you get things right without making any errors. For example, with the help of natural language processing, real-time language translation, speech recognition, and other support, professionals communicate quickly and conveniently.

6. Assists in Digital Marketing

As Machine Learning can help you gather vast resources of data, marketing your business gets more manageable. Today’s marketing is almost dependent on data. Now, it’s not just data, but the quality of the data also matters. Human resources cannot gather such a vast amount of clustered data. Machine Learning can help you collect customers’ data from various resources. When you have data at hand, you can create perfect marketing strategies for your business.

Besides, Machine algorithms help your marketing team easily predict the marketing trends and sense the current marketing traits. Identifying trends will enable them to make a better and informed decision, keeping even narrow marketing things in mind.

Top Industries for which Machine Learning is Beneficial For

Machine learning is for every business, whether it is startup, SMEs, enterprises, or retails, manufacturing, fashion, healthcare and logistics. Let’s explore the top sectors that can reap the benefits of Machine Learning.

1. Logistics

Artificial Intelligence machines powered by ML are set to disrupt the logistic sector. In fact, it has already begun. If you are wondering how then the autonomous vehicle is the answer. In the coming days, scheduling, route finding, cargo, and others will be efficiently done by AI/ML solutions.

2. Cybersecurity

Cybersecurity can be the most benefited industry with AI/ML and will have plenty of AI use cases. For example, cyberattacks have an AI-based angle, and AI can help businesses with risk management. From proactive and continuous surveillance to a real-time and risk management approach, AI tools powered by advanced machine learning apps will help the sectors make cybersecurity more dynamic and objective.

3. Healthcare

Healthcare is already reaping the benefits of AI, and its impact is going to be tremendous in no time. Basically, two significant usages of AI are magnificent.

For example;

  • AI has the ability to detect life-threatening diseases, like cancer
  • AI can help accelerate the drug discovery process

These two potentials of AI will help healthcare provide better healthcare facilities to patients and save more lives. Besides, machine learning apps will assist surgeons in OR and remote patients treatment facilities. Telemedicine is part of it.

4. Financial Services

The banking and financial sectors are already using AI and ML in their business processes. We have already mentioned that around 58% of fintech sectors use AI and ML solutions for fraud detection. However, there are various use cases of Machine Learning apps in the banking and financial sectors.

5. E-Commerce

If you have purchased products from Amazon, you must have realized repeat suggestions for the products you explored or have kept in your wishlists. AI and ML are playing a vital role in helping the platform gather consumer buying behavior and suggesting to customers the relevant products when you log in to the forum a second time.

6. Manufacturing

Product optimization and maintenance are crucial for manufacturing sectors, and AI is already providing colossal help. AI with a Machine learning app can help industrial and manufacturing organizations by detecting unusual signs and patterns. These will help industries with predictive maintenance. Meanwhile, manufacturing sectors with this predictive analysis can stop machinery failure much in advance.

Final Thoughts

Machine Learning is the future of almost all sectors and whether it is manufacturing, healthcare, retails, fashion, entertainment or others to get benefits of the advent. So, if you have embraced the technologies, you are on time or else it’s time to integrate the solution into your business process.

We at Dash Technologies offer comprehensive Artificial Intelligence and Machine Learning Software Solutions apart from customization, integration and dedicated ML app development. Let’s connect today and find out how Machine Learning can be the best contributor to your business success.

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