Machine learning has been around for decades, but in the age of big data, this type of artificial intelligence is in ever-increasing demand. Why? Simply put, businesses need help to view and manipulate the vast amounts of data that systems are currently generating on an ongoing basis.
Machine learning with a sound knowledge after learning dedicated courses suggested by TangoLearn, allows businesses to quickly create models that process large amounts of data and “learn” how to use them. Let’s have a look at some of the usages of machine learning across the industry.
Machine Learning Use Cases
Machine learning applications and uses are diverse and surround us every day.
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Recommendations
Recommendations for established streaming platforms such as Spotify and Netflix are founded on machine learning algorithms. These algorithms identify and suggest additional content of your choice by analyzing what you hear or watch, along with a variety of data about other songs, shows, and consumer habits.
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Fraud Detection
Using a machine learning model, banks and other financial institutions get the ability to detect frauds. Fraud Detection with Machine Learning becomes possible as machine learning algorithms help to learn from historical fraud patterns. These algorithms are effective than humans when it comes to the speed of information processing and help in finding frauds that humans cannot detect.
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Search Engine Results
Each time you enter a search term in Google, machine learning algorithms analyze your behavior to improve the future delivery of your results. For example, if you spend a long time on a website that isn’t ranked high on the first page of results, Google algorithms may promote that page to high on similar or related searches in the future.
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Chatbot Chat
AI-based assistant to solve problems online and a trained machine learning model will work to provide you with the right answers based on your input.
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Customer Retention
Service providers use machine learning models to identify customers who are willing to move their business elsewhere. If you stop using your credit card and suddenly receive an email offer to lower your APR, your credit card provider may be trying to build customer loyalty with the help of a machine learning platform.
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Candidate Screening
For companies that get hundreds of answers for each job listing, machine learning algorithms can help you search your resume for specific keywords and identify the best candidates for your interview.
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Real Estate Ratings
By analyzing the available data on the characteristics of homes and the sales of similar homes in the area, machine learning algorithms estimate the current value of the real estate on sites such as Zillow and Redfin.
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Learning App
Learning tools such as the Duolingo Language Platform benefits students with machine learning models learning to interpret data obtained from users and pace the course as desired.
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Spam Filter
By analyzing the characteristics of the subject, message text, and sender address, machine learning algorithms help protect your inbox from unwanted emails.
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Medical Imaging
Radiology can train machine learning platforms to identify potential X-ray problems in patients and show that further attention is needed.
What are the benefits of machine learning?
The use of machine learning shows how useful technology can be for businesses of all kinds. Regardless of where machine learning is used or how it is used, companies are explaining its benefits in terms of exponential profits and improvements. For further information regarding machine learning, click here.
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Make Faster Decisions
By enabling companies to process and analyze data faster than ever before, machine learning enables faster decision-making in the blink of an eye. For example, machine learning-based software trained to detect anomalies in a company’s security environment can immediately detect data breaches and notify the company’s technical team. These platforms help companies protect customer data, protect their business reputation, and avoid costly corrective actions by making swift decisions about effective corrective actions.
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More Accurately Predicting Demand
Companies are under pressure to forecast market trends and customer behavior in order to compete in a rapidly changing business environment. Incorporating machine learning models into data analysis gives enterprises much more accurate and powerful forecasting capabilities for more effective inventory management and significant cost savings.
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Customer Loyalty Personalization
Personalization is also an important strategy for competing in today’s market. With a machine learning platform that analyzes user behavior and suggests additional products based on purchase history, online retailers can interact with customers in a more personalized way and increase sales. Amazon, the global giant, is a prime example of using machine learning to create a list of recommended products and offer suggestions to customers.
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Increased Efficiency
Machine Learning can help businesses accelerate repetitive tasks and shift talent to higher-value jobs. For example, machine learning models can perform extensive document searches in a fraction of the time it takes humans to perform scanning and cross-reference tasks. These features allow organizations to reduce the cost of information retrieval activities related to regulatory compliance and legal research while allowing employees to focus on other activities.
Organizations that manage and maintain their investments more effectively can find it difficult to accurately assess when an investment requires maintenance or upgrades, which can be costly. Predictive machine learning models allow enterprises to collect performance data from devices and components to monitor the state and calculate the remaining life of an asset.
