With all the talk around big data – machine learning and artificial intelligence (AI) – organizations are now becoming more aware of the applications and benefits of machine learning in business.
Many people have probably heard of machine learning but don’t know what it is, what business-related problems it can solve or the value it can add to their business.
With Google, Amazon and Microsoft Azure launching their cloud machine learning platforms, AI and machine learning have gained prominence in recent years. There are many jobs in machine learning, including business managers, data scientists and DevOps engineers.
What is machine learning?
According to IBM, machine learning is a branch of AI and computer science that focuses on using data and algorithms to imitate how humans learn, gradually improving its accuracy.
Machine learning extracts meaningful insights from raw data to solve complex, data-rich business problems quickly. Machine learning algorithms learn from data iteratively and allow computers to find different types of hidden insights without being explicitly programmed to do so.
Machine learning is adapting and evolving quickly, helping organizations improve their scalability and business performance globally. Machine learning is a significant component of many organizations today, mainly as businesses across almost all sectors use various machine learning technologies.
Many use cases are emerging from all sectors as machine learning is implemented in education, logistics, manufacturing, hospitality, travel and tourism and energy.
Real-world machine learning applications
Real-time chatbots
Chatbots are one of the most used forms of automation today. They have closed the communication gap between humans and technology, making it possible to communicate with machines that can execute actions according to the requirements or requests voiced by the consumer.
At first, chatbots were only designed to follow scripted rules that instructed the bots on what actions to execute based on specific keywords. Today, machine learning and natural language processing, both parts of AI, enable chatbots to be more productive and interactive. Chatbots respond more efficiently to users’ needs and communicate increasingly more human-like.
Easy spam detection
Spam is promotional messages that are sent via the internet. These emails could be junk mail or simply annoying to customers, which can sometimes slow down computer performance.
Email providers made use of rule-based techniques to filter out spam. But thanks to machine learning, spam filters are making new rules using brain-line neural networks to eliminate spam mail. The neural networks recognize phishing messages and junk mail by evaluating the rules across a vast network of computers.
Faster decision-making
Machine learning allows for rapid decision-making by enabling companies to analyze and process data faster than ever. For example, machine learning-based software can identify any abnormalities in a firm’s security environment and quickly notify the company’s tech team when there is a data breach.
These platforms enable quick assessments of effective recovery solutions to assist organizations in protecting consumer information, preserving their reputation and avoiding costly corrective actions making it one of the most essential machine learning benefits.
Conclusion
Machine learning is becoming an essential part of big data that is being implemented throughout all business sectors to solve complex business problems while improving the effectiveness and scalability of an organization.
This is why organizations are looking to machine learning to improve accuracy, reduce errors, fast-track the work process and make the overall experience enjoyable for employees and customers.
Interested in learning more about the world of artificial intelligence?
Canadian College of Business and Technology’s Diploma in Data Engineering and Analytics will help students gain the knowledge, practical experience and confidence of a data expert. Data engineers transform raw data into readily accessible data for machine learning, AI and analytics systems.
Trebas Institute Montreal’s Analytics, Big Data and Business Intelligence program will give students the ability to set up networked and automated databases, operate data warehouses, perform refined analyses and produce detailed reports.
Toronto School of Management’s Diploma in Data Analytics helps students to learn to analyze data using cutting-edge technology to drive proactive decision-making and optimize business performance.