Summary

Summary

In this learning path, you learned the concepts and topics of machine learning, then applied them by building models and using them in apps. This learning path covered:

• Supervised versus unsupervised learning
• Data exploration and preprocessing
• Classification models
• Linear regression
• Classification-based machine learning problems
• Clustering algorithms

Next steps

Continue your learning and building your machine learning skills with more how-to tutorials and articles on the IBM Developer machine learning hub.

You can also work through this guided project, which takes a straightforward approach to show you the magic of embeddable AI. It also teaches you how to use Flask to deploy machine-learning models, so anyone can interact with them through an excellent user interface and know what you have accomplished. Perfect for developers with experience in Python and html, but struggling to implement ML models in their applications. Bridge the gap and take your business to the next level with this easy-to-follow project!