How Machine Learning Powers Business Growth

Kinley

Businesses of all sizes should consider investing in machine learning – or risking out on valuable data-driven insights that could help them beat their competition. Machine learning (ML) is one of the most powerful business transformation trends in 2018. Though increasingly complex to implement, ML empowers data-first companies in many ways — from increased performance and enhanced security to a considerable boost in ROI and revenue. Before investing, however, every business leader should be aware of the potential benefits of machine learning for their business, as well as how to solve business problems with ML.

Companies that don’t take advantage of ML risk staying on the technology sidelines – or even losing to their competition. You can use this article to how ML works and how it can impact your europe mobile number list business. What Is Machine Learning? Machine learning is a specific field of artificial intelligence (AI), that trains machines how to learn by “feeding” data (including Big Data) to their algorithms. Diagram showing how machine learning works The algorithms collect and process data using statistics to predict outcomes, generate insights, and unveil solutions to existing or potential problems. Specifically, data is prepared and modeled based on a company’s understanding of business goals and data. If the data is sufficient, it’s evaluated and deployed. If not, it gets reworked and enhanced to be deployed in a future cycle. When data is deployed, it is virtually run through an algorithm that checks how it behaves, generating predictions that allow businesses to make decisions and achieve specific results.



For instance, data can be put into an ML-powered user behavior algorithm that precisely predicts user intent. Many companies store large volumes of data that cannot be processed manually. If your company has 1 terabyte of data, it’s the equivalent of approximately 200,000 songs or 17,000 hours of music. By investing in ML, your business will gain the ability to continuously analyze this high volume of granular and extremely diverse unstructured data, gaining a strong competitive advantage.