Linear Algebra and Feature Selection

Linear algebra is a centuries-old field of mathematics, involving the application of vectors, matrices, and linear transforms. Nowadays, it takes an important role in shaping the world of machine learning. Feature selection – another key concept we will cover – detects unneeded variables in a machine learning model and linear algebra. Explaining the calculations behind an ML algorithm can be extremely useful in identifying the most efficient approach to manipulating data. This course will teach you the mathematical concepts behind linear algebra for machine learning and will show you how to integrate these concepts into the feature selection activity.

Introducing you to the essentials of machine learning in Excel with hands-on projects. You will use linear and logistic regression, k-means clustering, decision trees, and Azure ML Studio.