Description
In this course, you will learn:
- Understand how machine learning differs from other statistical models.
- Build tree-based models, support vector machines, and neural networks to hone your skills.
- In Python, implement theoretic models in machine learning software packages.
- Use machine learning models to solve problems in the workplace.
Syllabus:
- Decision trees
- Random forests and support vector machines
- Support vector machines
- Neural networks
- Neural network estimation and pitfalls
- Model comparison