Free Unsupervised Learning Course

Introduction to Unsupervised Learning

star 4.63  Beginner level 1.5 learning hrs 1.2K+ Learners

Learn unsupervised learning from basics in this free online training. Unsupervised learning course is taught hands-on by experts. Best for beginners. Learn about unsupervised learning & clustering in detail. Enroll for free now!

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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.

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Course outline

Introduction to Unsupervised Learning and Clustering

This module starts by introducing you to unsupervised learning. Next, you will learn about clustering and go through its applications.

 

Clustering - Types and Distance

K-means Clustering

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Introduction to Unsupervised Learning

rating icon 4.63

1.5 Hours

Beginner

1.2K+ learners enrolled so far

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Master in-demand skills & tools

Test your skills with quizzes

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Learner reviews of the Free Courses

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Reviewer Profile
Syeda Maria Azfar

5.0

★★★★ ★
“In-Depth Explanation of Unsupervised Learning”
Basics were cleared in depth. The course was easy to follow and grasp.
Reviewer Profile

5.0

★★★★ ★
Singapore
“The lessons are instructive and easy to follow”
Even without prior knowledge and experience in this area, I can still follow the lessons.
Reviewer Profile

5.0

★★★★ ★
India
“I enjoyed the interactive approach and practical examples, which made complex topics easier to understand.”
I really appreciated the clear explanations and how the learning material was presented in a structured manner. The practical exercises helped reinforce the concepts and made the experience highly engaging. It was an enjoyable and valuable learning process!
Reviewer Profile

5.0

★★★★ ★
“High quality presentation, Flexibility of the platform”
High quality presentation, Flexibility of the platform, good professor
Reviewer Profile

5.0

★★★★ ★
“It was very informative and interesting.”
Email spam filtering is an essential application of supervised learning in machine learning. By analyzing labeled datasets containing both spam and non-spam emails, algorithms learn patterns and characteristics that distinguish the two categories. This enables them to automatically classify new incoming emails, reducing unwanted content and improving user experience in email management.
Reviewer Profile

5.0

★★★★ ★
India
“Good courses and enjoy this learning”
Greate learning experience with this course very useful learning video and quick learning
Reviewer Profile

5.0

★★★★ ★
India
“good for machine learning topic unsupervised”
very good learing website for machine learning is to understand
Reviewer Profile

5.0

★★★★ ★
India
“Understanding concept videos and quize is very usefull”
Understanding concept videos and quize is very usefull and
Reviewer Profile

5.0

★★★★ ★
Philippines
“The title of the course is unsupervised learning”
The topic id depth and the quizzes and assignments is analytical but easy to follow
Reviewer Profile

5.0

★★★★ ★
India
“Introduction to unsupervised machine learning ”
Very informative

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