Machine learning is part many of cool features in the high-tech products we have today. But what can machine learning do? What are some of the use cases for machine learning?

• Determine which of your customers are likely to churn
• Detect which transactions are likely to be fraudulent
• Detect credit card fraud
• Predict the likelihood of an insurance claim being fraudulent.
• Segment customers and find the best marketing strategy for each group.
• Forecast next quarter’s sales
• Filter you email for spam
• Perform speech recognition
• Detect tumors in medical image scans
• Automatically classify articles
• Summarize long documents
• Make product recommendations on an ecommerce site

Machine learning is used in all kinds of industries. It’s used in healthcare, finance, transportation, retail and many others.

Finance

Machine learning is being used to make predictions about the stock market. It is also being used to detect fraudulent activity in financial transactions.

Healthcare

In the healthcare industry machine learning can provide doctors with tools to improve patient outcomes. For example, machine learning can analyze medical images to identify signs of disease, leading to earlier diagnosis and earlier treatment. It can also be used to analyze a patient’s history to come up with a plan of care, given their genetics. This can result in better treatments that maximize effectiveness and minimize side effects or allergic reactions.

Transportation

Machine learning can be used to optimize traffic patterns with the synchronization of traffic lights, for example. It can improve the safety of autonomous vehicles. Data from sensors and cameras can be used by machine learning models to suggest a route to take for faster arrival times and higher safety.

Retail

Machine learning can be used in retail to improve the customer experience by making suggestions based on that customer’s buying patterns. It can suggest similar products. In retail, machine learning can be used to optimize inventory management be predicting when products will sell out and recommend the time and amount to purchase. The food industry can have less waste by reducing the number of products that expire.

Education

Machine learning can personalize learning experiences for students. Strengths and weaknesses can be analyzed to develop learning suggestions. It can also predict which students are most likely to drop out. Additional support can then be allocated.

Marketing

Machine learning is being used in the marketing industry to improve the effectiveness of advertising campaigns. Machine learning is also being used to develop predictive models that can identify which customers are most likely to make a purchase.