Machine Learning 102: Clustering

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 special series “Oracle Machine Learning Office Hours – Machine Learning 101”, where we will go through the main steps of solving a Business Problem from beginning to end, using the different components available in Oracle Machine Learning: programming languages and interfaces, including Notebooks with SQL, UI, and languages like R and Python.

This sixth session in the series covered Clustering 102, where we learn more about the methods on multiple dimensions, how to compare Cluster techniques, and explore Dimensionality Reduction and how to extract only the most meaningful attributes from datasets with lots of attributes (or derived attributes).

Transcript

1. With Marcos Arancibia, Product Manager, Data Science and Big Data @MarcosArancibia Mark Hornick, Senior Director, Product Management, Data Science and Machine Learning @MarkHornick oracle.com/machine-learning Oracle Machine Learning Office Hours Machine Learning 102 - Clustering Copyright © 2020, Oracle and/or its affiliates. All rights reserved
2. Today’s Agenda Upcoming session Speaker Marcos Arancibia – Machine Learning 102: Clustering Q&A Copyright © 2020 Oracle and/or its affiliates.
3. Next Session December 3, 2020: Oracle Machine Office Hours, 8AM US Pacific Machine Learning 101 – Feature Extraction 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 special series “Oracle Machine Learning Office Hours – Machine Learning 101”, where we will go through the main steps of solving a Business Problem from beginning to end, using the different components available in Oracle Machine Learning: programming languages and interfaces, including Notebooks with SQL, UI, and languages like R and Python. This seventh session in the series will cover Feature Extraction 101, and we will learn more about the methods to extract meaningful attributes from a large number of columns in datasets, explore Dimensionality Reduction and how it can be beneficial as a pre-processing for Machine Learning models. Copyright © 2020, Oracle and/or its affiliates. All rights reserved
4. For product info… https://www.oracle.com/machine-learning Copyright © 2020 Oracle and/or its affiliates.
5. Copyright © 2020 Oracle and/or its affiliates. https://www.oracle.com/cloud/free/
6. Today’s Session: Machine Learning 102 - Clustering In this "ML Clustering 102" we will study the effect of multiple variables in clustering, and we will learn more about the methods on multiple dimensions, compare Cluster techniques, and explore Dimensionality Reduction and how to extract only the most meaningful attributes from datasets with lots of attributes (or derived attributes). Copyright © 2020, Oracle and/or its affiliates. All rights reserved
7. Copyright © 2020, Oracle and/or its affiliates 7 Demo on OML4Py, Clustering on 3+ dimensions: Visit the Recording at: https://asktom.oracle.com/pls/apex/asktom.search?oh=10715
8. For more information… oracle.com/machine-learning Copyright © 2020 Oracle and/or its affiliates.
9. Copyright © 2020, Oracle and/or its affiliates 9 Q & A
10. Thank You Marcos Arancibia | marcos.arancibia@oracle.com Mark Hornick | mark.hornick@oracle.com Oracle Machine Learning Product Management