About This Course
This course covers the essential concepts of statistical analyses and mathematical modeling, introducing terminology and core algorithms from the field of machine learning. You'll gain hands-on experience with linear models for classification and regression, including data preprocessing, dimensionality reduction, model selection, feature selection, model construction and regularization. We’ll construct models using data from a variety of application domains.
What You’ll Learn
- Foundational concepts from linear algebra, probability, calculus and statistics
- Linear, graphical, nearest neighbor and generalized additive models
- Model building, evaluation, tuning and performance improvement
Get Hands-On Experience
You’ll practice working with open-source tools such as Anaconda3, Python and scikit-learn.
