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25 Jun 2014

Application of Clustering in Data Science Using Real-Time Examples

The above video is the recorded session of the webinar on the topic “Application of Clustering in Data Science Using Real-Time Examples”, which was conducted on 28th June’14.

Introduction to Application of Clustering in Data Science

Clustering data into subsets is an important task for many data science applications. It is considered as one of the most important unsupervised learning technique. Keeping this in mind, we have come with a video that explains this with real life examples.

Topics included in this Video:

  • What is Data Science?
  • What is Clustering?
  • What is K-means clustering?
  • Examples of k-means clustering in real-life Data Science Applications.

Watch a Presentation on this Topic:

As you are aware, Clustering is “the process of organizing objects into groups whose members are similar in some way”. Let’s look at some of the reasons to go for clustering and where to use them.

clustering-edurekaWhy Clustering?

Clustering can be done for the following reasons:

  • Simplifications
  • Pattern detection
  • Useful in data concept construction
  • Unsupervised learning process

Where to use Clustering?

  • Data Mining

  • Information Retrieval
  • Text mining
  • Web Analysis
  • Marketing
  • Medical Diagnostic

Edureka has a specially curated Data Science Training Course that helps you gain expertise in Machine Learning Algorithms like K-Means Clustering, Decision Trees, Random Forest, and Naive Bayes. You’ll learn the concepts of Statistics, Time Series, Text Mining, and an introduction to Deep Learning as well. You’ll solve real-life case studies on Media, Healthcare, Social Media, Aviation, and HR. New batches for this course are starting soon!!

Ready to supercharge your career in data science? Don’t miss out on the opportunity to earn your Data Science with Python Certification. With this certification, you’ll gain the skills and knowledge needed to excel in the world of data analysis, machine learning, and predictive modeling. Take the first step toward a brighter future in data science – enroll now, study diligently, and earn your certification to open doors to exciting career opportunities. Get started today and unlock your potential in the data-driven world!

Got a question for us? Mention them in the comments section and we will get back to you.

Related Posts:

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Advantages of Data Science Training




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