**28+ Machine Learning Versus Statistical Modeling Images**. What is the difference between predictive modeling and machine learning? How is statistics used in machine learning?

See full list on educba.com Since machine learning algorithms learn from data, they can be used more effectively when there is a large volume of information available. This is an important point of distinction between the two domains.

### Where machine learning is a broad discipline that encompasses how computers can understand and “learn” from data, statistical learning focuses on taking raw data and turning it into actionable information, and it is the basis for machine learning algorithms.

In statistical modeling, we pay heed to a lot of uncertainty estimates (like confidence intervals, hypothesis tests)and we have to take into account that all of the assumptions have to be satisfied before we can trust the outcome from a particular algorithm. In applied statistics (astat)for data professionals interested in earning an advanced degree without interrupting the rest of their careers. Machine learning is one of the fields in data science and statistics is the base for any machine learning models. Chatbots and machine learning systems are trained to respond to the most common user complaints and questions, allowing companies to focus their customer service agents on addressing complex or highly escalated cases.