Machine Learning 102: Classification

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. Video Highlights 01:01 Web Questions 01:30 Next session announcement: 101 Regression 02:21 Machine Learning 102 - Classification 03:30 Review on model evaluation 06:11 Confusion Matrix 07:05 Lift/Gains Chart 19:57 Decile lift chart using Python in OML4Py 22:35 Density of Predictions compared using Python in OML4Py 26:10 ROC curve using Python in OML4Py 30:49 Demo Machine Learning 102 - Classification 32:15 Data loading and processing 34:00 Python function to automate OML4Py model build 38:13 Python function to automate OML4Py model evaluation 47:05 Decision Tree model evaluation 49:31 Naive Bayes model evaluation 50:00 Logistic Regression model evaluation 50:42 Logistic Regression (with feature generation and selection) model evaluation 51:35 Random Forest model evaluation 52:36 Support Vector Machines model evaluation 53:32 Neural Networks model evaluation 54:09 AutoML 54:40 Final summary of all models 55:32 Q&A AskTOM Office Hours offers free, monthly training and tips on how to make the most of Oracle Database, from Oracle product managers, developers and evangelists. https://asktom.oracle.com/ Oracle Developers portal: https://developer.oracle.com/ Sign up for an Oracle Cloud trial: https://www.oracle.com/cloud/free/