Wrap Up: Machine Learning Basics¶
You’ve just completed the Machine Learning Basics course, where you gained experience in working with visual machine learning in Dataiku DSS.
Here are a few of the main takeaways from this course:
You discovered ways to prepare a dataset for machine learning, look for potential issues in your data, and select and create features.
You learned how to create quick prototypes that can be used as iterative starting points for modeling.
In the Design Tab and Result Tab concept videos, you discovered ways to modify your model’s design and track its performance, all with the goal of generating the best possible results.
Then you learned about tuning the model, including how to handle different features, and optimize hyperparameters.
Finally, the Explainable AI section introduced ways to build trustworthy, transparent, and bias-free models.
Be sure to check out other Academy courses! The next course in the Visual Machine Learning course series is Scoring Basics. You can also continue your AI learning journey with more ML Practitioner courses like Interactive Visual Statistics, Image Classification, and Natural Language Processing.