The A to Z of Unsupervised ML

  • IntermediateLevel

  • 1500+Students Enrolled

  • 1 HrDuration

  • 4.8Average Rating

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About this Course

  • Unsupervised ML reveals hidden patterns in data, vital for exploratory analysis and discovering relationships without labeled examples.
  • Mastering unsupervised techniques boosts data preprocessing and insights in complex datasets with scarce labels
  • Gain hands-on experience with exercises to apply unsupervised ML concepts and build real-world models.

Learning Outcomes

Exploratory Data Analysis

Utilize unsupervised learning to perform in-depth data analysis.

Master Unsupervised ML

Learn unsupervised techniques to reduce complexity.

Hands-On Learning

Engaging exercises to apply unsupervised ML concepts to real-world.

Who Should Enroll

  • Professionals: Expand your skill set and apply unsupervised learning in diverse industries for better insights.
  • Aspiring Students: Begin your machine learning journey and build a strong foundation for a career in tech
  • Tech Enthusiasts: Dive into the world of unsupervised learning and explore its real-world applications across fields.

Course Curriculum

Explore a comprehensive curriculum covering Python, machine learning models, deep learning techniques, and AI applications.

tools

  1. 1. Resources to be used in this course.

  2. 2. Setting the Context

  3. 3. Choosing Clustering Algorithms

  4. 4. Solving our Problem using k-means - Part 1

  5. 5. Solving our Problem using k-means - Part 2

  6. 6. Finding optimal K valuel

  7. 7. Analysis and Insights Based on the Plots

  8. 8. Introduction to Hierarchical Clustering Analysis (HCA)

  9. 9. Solving our Problem using Hierarchical Clustering

  10. 10. Introduction to DBSCAN Clustering", "Solving our Problem using DBSCAN

  11. 11. Reading: Applications of Clustering in the Real World

  12. 12. Project Hands On

Meet the instructor

Our instructor and mentors carry years of experience in data industry

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Apoorv Vishnoi

Head - Training, Analytics Vidhya

Apoorv is a seasoned AI professional with over 14 years of experience. He has founded companies, worked at start-ups and mentored start-ups at incubation cells.

Get this Course Now

With this course you’ll get

  • 1 Hour

    Duration

  • Apoorv Vishnoi

    Instructor

  • Intermediate

    Level

Certificate of completion

Earn a professional certificate upon course completion

  • Globally recognized certificate
  • Verifiable online credential
  • Enhances professional credibility
certificate

Frequently Asked Questions

Looking for answers to other questions?

Unsupervised machine learning helps uncover hidden patterns and structures in data without labeled examples. It is essential for exploratory data analysis, reducing dimensionality, and discovering intrinsic relationships within datasets. Mastering unsupervised techniques enhances data preprocessing and drives insights in complex datasets where labels are scarce or unavailable.

This course is free of cost.

The course will teach you how to use unsupervised learning to explore data, identify patterns, and visualize relationships between features, making it easier to gain insights from complex datasets.

Yes, the course covers how unsupervised techniques can be used in feature engineering, especially when it comes to transforming or creating features that can enhance the performance of machine learning models.

Unlike supervised learning, which uses labeled data to train models, unsupervised learning works with unlabeled data to identify patterns, clusters, and hidden relationships without the need for predefined labels.x

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