Mathematics for Machine Learning. Learn about the prerequisite mathematics for applications in data science and machine learning.

• Recall how machine learning and vectors and matrices are related
• Interpret how changes in the model parameters affect the quality of the fit to the training data
• Recognize that variations in the model parameters are vectors on the response surface – that vectors are a generic concept not limited to a physical real space
• Use substitution / elimination to solve a fairly easy linear algebra problem
• Understand how to add vectors and multiply by a scalar number
• 10 Student per Batch.
• One to one option avalible.