Machine learning (ML) is the process of using mathematical models of data to help a computer learn without direct instruction. It’s considered a subset of artificial intelligence (AI). Machine learning uses algorithms to identify patterns within data, and those patterns are then used to create a data model that can make predictions. With increased data and experience, the results of machine learning are more accurate—much like how humans improve with more practice.
The adaptability of machine learning makes it a great choice in scenarios where the data is always changing, the nature of the request or task is always shifting, or coding a solution would be effectively impossible. Machine learning has many applications and the possibilities are constantly expanding. Let’s dive into how Azure Machine Learning is helping individuals, teams, and organisations meet and exceed business goals.
Machine learning can help identify a pattern or structure within both structured and unstructured data, helping to identify the story the data is telling.
Adaptive interfaces, targeted content, chatbots, and voice-enabled virtual assistants are all examples of how machine learning can help optimize the customer experience.
Machine learning can mine customer-related data to help identify patterns and behaviors, letting you optimize product recommendations and provide the best customer experience possible.
Machine learning is excellent at data mining and can take it a step further, improving its abilities over time
As fraud tactics constantly change, machine learning keeps pace—monitoring and identifying new patterns to catch attempts before they’re successful.
One machine learning application is process automation, which can free up time and resources, allowing your team to focus on what matters most.
Learn how to train, deploy, & manage machine learning models, use AutoML, and run pipelines at scale with Azure Machine Learning. Sign up for our Azure Data Analytics and Machine Learning Bootcamp today!