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.