Interested in Machine Learning? Join us at this webinar where we compare different clustering algorithms with a detailed walk-through of each of them with a hands-on experience.
Clustering is the assignment of a set of observations into subsets (called clusters) so that observations in the same cluster are similar in some sense. It is a method of unsupervised learning and a common technique for statistical data analysis used in many fields.
Categories of clustering algorithms we will be discussing:
- Centroid-based clustering
- Density-based clustering
- Hierarchical clustering
In this webinar, scikit-learn provides data sets that help to illustrate the clustering algorithm differences. We’ll use these where needed, but we also use our customer data set to help you visualize clustering with realistic data instead of obvious shapes.
- Watson Studio
Prerequisites & Required Installations:
- IBM Cloud Account – Login in or Sign up at https://ibm.biz/ClusteringWebinar
- Register for the live stream here: xxx
- 10:00PM – 10:10PM —> On-boarding and Signups
- 10:10PM – 10:40PM —> Intro to Clustering Algorithms
- 11:40PM – 12:00AM —> Walk-through & Questions
After the webinar the recording will be made available on Youtube: https://www.youtube.com/user/IBMMEA/videos
- Mridul Bhandari
- Fawaz Siddiqi
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Dubai, United Arab Emirates