This course dives into the basics of Machine Learning using an approachable, and well-known programming language, Python. We will be reviewing two main components:
- The purpose of Machine Learning and where it applies to the real world.
- A general overview of Machine Learning topics, such as supervised vs unsupervised learning, model evaluation, and Machine Learning algorithms.
In this course, you will:
- Explore examples of Machine Learning and the libraries and languages used to create them.
- Apply the appropriate form of regression to a data set for estimation.
- Apply an appropriate classification method for a particular Machine Learning challenge.
- Use the correct clustering algorithms on different data sets.
- Explain how recommendation systems work, and implement one on a data set.
- Demonstrate your understanding of Machine Learning in an assessed project.