What is Machine Learning?
Machine Learning is a set of artificial intelligence techniques that gives web and mobile applications the ability to learn, adapt, and improve over time. It does this by processing vast amounts of data, identifying trends and patterns within it – most of which would not be apparent to a human being – and then making decisions and taking actions to help meet specific objectives.
Why do you need Machine Learning?
Machine Learning opens your business to a wide variety of new opportunities. You can personalize your customer experience, automate processes, and implement solutions that will change the way customers interact with your product.
Machine Learning is widely applied to business problems, reducing companies’ costs and increasing customer satisfaction. ML algorithms can be used in applications across practically all sectors – from ecommerce to finance, healthcare to education, cybersecurity to charity.
What are the best Machine Learning examples?
Machine Learning can be used in various business sectors - both B2B and B2C companies can benefit from it.
Amazon’s ML-powered recommendation engine drives 35% of total sales. Thanks to the AI-Bot Harry, AXA saves roughly 17,000 man-hours a year. At the same time Vodafone noticed a 68% improvement in customer satisfaction after introducing its Machine Learning chatbot TOBi.
American Express and PayPal detect fraud in real time by quickly analyzing millions of transactions to pinpoint which charges aren’t real. The quick service means customers can resolve the problem almost instantly.
Researchers based at UCLA managed to identify cancer cells with over 95% accuracy after equipping a special microscope with Machine Learning algorithms. Maybe that is why 69% of college-aged individuals would want AI involved in their medical treatments.
Where can it be used?
Machine learning is used in different sectors: from retail and finance, through to healthcare, to education and charity. E-commerce and marketing leverage ML algorithms for their recommendation engines to cater for their users better. Hedge funds use ML to forecast stock prices, whereas insurance companies can calculate risk more accurately. Banks and other financial institutions, are able to detect suspicious transactions – also using Machine Learning. Medical companies use ML to diagnose medical conditions based on sets of symptoms.
Is Machine Learning something for your business?
Machine Learning projects are usually high-risk projects, due to their complex dependencies on data. That is why top Machine Learning companies offer feasibility studies to reduce the risk before engaging into the project: the data gets reviewed and confronted with project goals.