Have you always been curious about what machine learning can do for your business problem, but could never find the time to learn the practical necessary skills? Do you wish to learn what Classification, Regression, Clustering and Feature Extraction techniques do, and how to apply them using the Oracle Machine Learning family of products? Join us for this second chapter of the series “Oracle Machine Learning Office Hours – Machine Learning 101”.
In this "ML Classification 102" session we picked up where we left off from our 101 Session, and went deeper in our discussions on ML algorithms, the importance of Feature Selection, and explored even more the correct way to evaluate models using the Confusion Matrix and the many statistics that can be computed from it.
We continued to make use of Oracle Machine Learning Notebooks, with Python and SQL as the underlying languages and OML4Py with AutoML for our demo environment.