Machine Learning

Introduction to Unsupervised Learning


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About this course

Unsupervised learning is a very popular form of machine learning where the dataset is presented to the algorithm without having labels present. This means that the algorithm will have to find the underlying structure present in the data to make sense of it and learning based on the same. Unsupervised learning is used for machine vision, NLP, visualization, anomaly detections and a lot of other interesting and important applications. This course aims to provide you with information that will help you understand what unsupervised learning algorithms are and more importantly how they work to solve important problems around us.


  • Clustering
  • Principal Component Analysis (PCA)

Course Syllabus

Introduction to Unsupervised Learning

  • Introduction to Unsupervised Learning and Clustering
  • Clustering - Types and Distance
  • K-means Clustering

Course Certificate

Get Introduction to Unsupervised Learning course completion certificate from Great learning which you can share in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.

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