Online Courses and Training on Clustering
What is Clustering?
Clustering is a machine learning technique that helps group unlabelled datasets. It classifies data points into various clusters comprising similar data points. It identifies similarities and patterns in attributes like shape, size, behavior, and color, and separates the items according to the presence and absence of said patterns.
There are different clustering methods and each is used as per the required application. Broadly, they can be divided into hard clustering, where data points belong to one group only, and soft clustering, with data points belonging to various groups. In addition, other clustering approaches include partition clustering, density-based clustering, the distribution-model approach, hierarchical clustering, and fuzzy clustering.
Following clustering, each cluster is assigned a cluster ID whereby the entire feature set can be condensed. What makes clustering an even more potent tool in machine learning is its ability to represent complex examples using simple cluster IDs. Put simply, clustering simplifies large datasets and aids data analysis.
Why is Clustering Important?
In the present data-driven landscape where technology is an inextricable part of our daily lives, clustering finds myriad uses across various industries. Common applications include market segmentation, statistical data analysis, social network analysis, image segmentation, and anomaly detection among others. Giants like Amazon and Netflix employ clustering to refine their recommendations according to users’ histories.
Three Important Uses of Clustering:
- Generalization: In the case of examples in a cluster missing some data, other examples in the same cluster can help infer the missing data. For instance, less popular Youtube videos can be clustered with the more popular ones to improve recommendations and views.
- Data compression: As the feature data of all examples in a cluster can be replaced by the cluster ID, it simplifies the data and saves storage space, which is especially relevant to large data sets. Furthermore, cluster IDs can be used as input instead of the entire feature dataset, thus further simplifying the input data.
- Privacy: Clustering helps preserve privacy by clustering users and connecting user data to cluster IDs as opposed to specific users. However, to facilitate this, the cluster must group an adequate number of users to begin with.
Can I Learn About Clustering Online?
It is a wise decision to learn the fundamentals of clustering through online courses. Designed to cater to learners of all levels, online clustering courses are flexible, affordable, and offered by some of the most renowned global institutions. Many of them also provide certification which further boosts one’s employability and helps in career advancement.
How Can Learning about Clustering Improve My Career?
Clustering is an added skill in your machine learning and programming armoire. It will strengthen your resume and help you stand out from the crowd, as many leading companies seek ML specialists and experts to advance their growth and enhance efficiency.
Why Take an Online Course at Emeritus?
Each Emeritus online course is designed keeping key learning outcomes in mind by a team of experts. We use the backward design methodology to develop instruction for learners of all ages. This enables us to craft unique, interactive, learning experiences that include a combination of assessments, hands-on activities, skill application, and more.
Emeritus also collaborates with the best universities and faculty around the world to curate the course curriculum that can effectively tackle present challenges in the industry, while preparing you for the trends and risks in the future. Our courses consist of assignments, exams, capstone projects, networking opportunities, a fine balance of practical and theoretical concepts, and the opportunity to learn from top minds in the industry. This adds to the holistic experience we try to provide for each learner.
We are also focused on providing courses that are standardized in quality. This is done by adhering to standards set by a global organization called Quality Matters which is focused on providing quality standards for online and innovative digital teaching and learning environments. The rigorous criteria ensure all our learners invest in quality education that is easily accessible and affordable.
