Machine Learning: 6 Practical Applications of the Budding Technology

Machine learning is a novel and innovative technology that promises to revolutionize industrial and professional processes across various niches. It is a subset of artificial intelligence (AI) that uses statistical and computational techniques to develop intelligent digital systems that can learn from databases.

Machine learning programs allow businesses to analyze large datasets quickly to develop beneficial strategies and solutions. They can adjust to new conditions or changes since machine learning algorithms allow for adaptation without prior programming.

There are various applications for this technology, from reading emails to predicting future trends and market opportunities. Here are some of the most exciting practical applications of the technology being used today.

  1. Digital Personal Assistants

We all know of Siri, Google Now, and Alexa as some of the most popular virtual assistants on the market. These assistants help their users to find information, set reminders and schedule their day-to-day lives using voice-based commands. These programs will search for relevant information, recall previous queries you have made, and control other resources to fulfill your command.

Machine learning plays an important role in this technology, as using this technology, these programs can refine the information they provide you based on previous interactions. Your usage data can then be used to further refine the service they provide, delivering results that are better tailored to your requirements later on.

Ultimately, virtual personal assistants are becoming increasingly important in our day-to-day lives. We rely on them more than ever before, and the integration of machine learning is helping these systems to become more valuable to us with each passing day.

  1. Video Surveillance

The conventional way to monitor video feeds is for a single person to attempt to watch multiple screens simultaneously. This is a challenging task and is also exceptionally boring. However, with the advent of machine learning, it is now possible to train computer programs for this purpose.

Many video surveillance systems these days are powered by AI. Once a far-fetched Sci-Fi fantasy in films like Minority Report, machine learning can now identify crimes before they happen in some cases. AI video surveillance can track unusual behavior on video feeds. For example, if an individual has been standing still for a long time and acting suspiciously, the system can automatically flag this as potentially dangerous behavior.

Human attendants can then review the feed that has been flagged, ultimately helping to avoid mishaps and prevent crime. Additionally, the more the system successfully flags situations where there is genuinely suspicious activity, the more accurate it will become in the future. This is thanks to backend machine learning underlying the system.

  1. Filtering Emails

One of the more annoying aspects of the digital age we live in is the seemingly relentless spam emails that clog up our inboxes. Thankfully, machine learning provides solutions to this issue.

People that send out spam emails are constantly evolving and adapting their processes to bypass rule-based spam filters that individuals implement in their inboxes. Machine learning enables new and more effective methods for catching these potentially harmful emails.

Using past data, machine learning algorithms can filter out potentially harmful emails while adding scammers’ newer techniques to their databases. This helps email filters to stay up to date with the current trends and react to them, ultimately keeping you safer.

More than 450,000 new forms of malware are detected each day, but these tend to share between 90 and 98% of their code with previous iterations. Machine learning algorithms can recognize these coding patterns and detect malware resembling the same code’s older forms. Therefore, using machine learning in email filters can significantly boost cybersecurity.

  1. Better Search Results

Google and other search engines have begun to implement machine learning to show you results for your queries. Every time you search on the internet using Google, a backend algorithm will watch and analyze how you react to your results.

For example, if you open the top results and then stay on the ensuing website for an extended period, the search engine will assume that this website displayed relevant information to your query. On the other hand, if you get to the second or third page of results, the search engine will assume that the first results were irrelevant to the query. This can help search engines display more helpful information to users, streamlining our experience on the internet.

  1. Enhanced Customer Service

Many websites nowadays offer customers the opportunity to chat with a customer service representative while navigating the site itself. However, it is not always a real-life person that answers your queries. Most of the time, when you use these services, you are actually talking to a chatbot.

These automated chatbots extract the relevant information from the messages you send them and then present relevant information on the website to the customer.

With every passing moment, these chatbots become more advanced thanks to machine learning. They can understand user queries better and deliver better results thanks to the ever-evolving nature of machine learning algorithms.

  1. Fraud Detection

Another way machine learning promises to make using online services safer is in its applications for tracking internet fraud.

For example, PayPal, one of the world’s largest money exchange platforms, is integrating machine learning into its services to protect against money laundering. The company is implementing a set of tools that include machine learning algorithms to analyze and compare millions of transactions. Using past data, the systems can distinguish between legitimate and illegitimate transactions between buyers and sellers.

Suspicious transactions can then be flagged for investigation. If there are any illegitimate reasons for these transactions, such as moving ill-gotten money from place to place to launder it, PayPal can notify the relevant authorities.

How You Can Capitalize on Machine Learning

As stated above, there are myriad uses for machine learning across many different industries and markets. Therefore, you might be wondering how you can harness machine learning to improve your day-to-day operations.

One way that you can enhance your understanding of the technology is to gain a machine learning certification. Taking a machine learning course online can help you to understand the benefits of practical machine learning. Additionally, such machine learning courses are valuable for gaining knowledge of the technology’s processes. This can be a valuable resource for integrating things like machine learning analytics and automation into your operations.

Ultimately, taking a short course in London on the benefits and intricacies of machine learning can significantly boost productivity and efficiency within your operations. Additionally, with the advent of online teaching, it is now possible to earn a certificate in machine learning online. It can help you identify areas that can be streamlined by technology and free up time for more pressing matters.

The Takeaway

Overall, machine learning and AI are here to stay in the modern world, and their applications could change the world as we know it. From optimizing processes to identifying certain forms of cancer, machine learning has been touted as a powerful tool for the progression of humanity in the 21st century.

While some of its applications are still in their infancy stages, the technology is widely used across other facets of life. The use cases outlined above represent some of the practical applications of machine learning that are presently utilized but expect more developments in this field in the coming months and years.

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