There are two major categories of problems that are often solved by machine learning: regression and classification. Regression is for numeric data (e.g. What is the likely income for someone with ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

Businesspeople need to demand more from machine learning so they can connect data scientists’ work to relevant action. This requires basic machine learning literacy — what kinds of problems ...

Learn what is Linear Regression Cost Function in Machine Learning and how it is used. Linear Regression Cost function in ...

It's mostly useful to provide a baseline result for comparison with more powerful ML techniques such as logistic regression and k-nearest neighbors. Perceptron classification is arguably the most ...

While the course covers theories of Machine Learning and tools such as R, the focus is on using them for solving data-driven problems. The students will be introduced to several real-life problems ...

including Azure Machine Learning Studio, a browser-based user interface that organizes the data collection and analysis. Data can be augmented with labels and other classification using various ...