In this course, you will learn
- All about data and how it is critical to the success of your applied machine learning model.
- The critical elements of data in the learning, training and operation phases Understand biases and sources of data Implement techniques to improve the generality of your model
- How to turn generic data into successful fuel for specific machine learning projects. There are so many ways data can go wrong! This week discussed some of the pitfalls in data identification and processing.