Automated Machine Learning (AutoML) tools help in automating the end-to-end process that is involved in building and maintaining machine learning models. In this learning path, learn how AutoAI in Watson Studio can automatically prepare data, apply machine learning algorithms, perform hyperparameter optimization, and build model pipelines best suited for your data sets and use cases.
Try a Coursera trial to learn about, and become certified on, rapid prototyping with Watson AutoAI. To connect with your peers and discuss AutoML and other data science topics, join the IBM Data Science Community.
Estimated time to complete
Approximately 2 hours.
With this learning path, you get:
- An overview of Automated Machine Learning (AutoML)
- An introduction to AutoAI
- A comparison of model building with and without AutoAI
- How to generate the optimal model pipeline for your problem
- How to auto-generate a Python notebook using AutoAI
- How to quickly create your Python machine learning web app
- Information about automated feature engineering for relational data