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Unsupervised Machine Learning with K-means
4.42
Beginner level
2.25 learning hrs
Learn Unsupervised Machine Learning with K Means technique to analyse and cluster unlabelled dataset
Instructor:
Ms. Sampriti Chatterjee
About this course
Machine Learning is one of the most effectively used technology. Currently, all the companies are using this technology as they can use their data to understand the important areas from where they can grow their business. Machine learning uses two types of techniques. One is supervised machine learning that trains a model on known input and output data so that it can predict future outputs. The second called unsupervised learning finds hidden patterns or intrinsic structures in input data. Unsupervised Machine Learning with k-means is a popular technique that is used to analyze and cluster unlabeled datasets. Unsupervised learning methods are widely used in various machine learning techniques.
In this free course, you will be introduced to machine learning and its types, later, with the understanding of unsupervised learning. Next, you will learn unsupervised learning models, like K-means clustering. You will learn how to decide the K value and a demo on K-means clustering. NumPy, Pandas, and Scikit Learn Library are the skills you will learn in this course.
Some world-class universities, such as the University of Texas at Austin and SRM Institute of Science and Technology, have collaborated with Great Learning to create post-graduate Artificial Intelligence Courses and degree programs in India. A comprehensive and exhaustive curriculum has been designed by world-class faculty so that the learners can develop advanced skills in the AIML online course. Several industry experts from top-notch companies provide personalized mentorship to the learners to guide them in their successful career paths.
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Course outline
What is Machine Learning?
This module begins by defining machine learning. It then discusses how a machine understands the tasks with examples and explains supervised and unsupervised learning concepts in machine learning.
Types of Machine Learning
This section discusses Supervised and Unsupervised Machine Learning methods to accomplish various tasks.
What is Unsupervised Learning?
What is k-means Clustering?
How to decide the K Value?
Get access to the complete curriculum once you enroll in the course
4.42
Our course instructor
Ms. Sampriti Chatterjee
Machine Learning Expert
Frequently Asked Questions
Will I receive a certificate upon completing this free course?
Is this course free?
What are some prerequisites to learn unsupervised machine learning?
Algebra, linear algebra, trigonometry, statistics, calculus, python programming, and cloud console are some of the important concepts in unsupervised machine learning thus making them essential topics to have hold on to understand the subject better. It is suggested to learn these topics before you dive into learning unsupervised machine learning.
How do beginners learn unsupervised machine learning?
Beginners have to start with understanding basic mathematical concepts required for unsupervised machine learning. If you are not already experienced in coding, then you must also have to learn programming, Python recommended. It is also important to understand machine learning concepts. So you can begin learning Python and machine learning for beginners before you dive into an unsupervised machine learning course.
How long does it take to learn unsupervised machine learning?
If you are already aware of all the concepts that you need to understand unsupervised learning, and if you already have a thorough understanding of all these concepts, then it will take anywhere from three to four weeks to master unsupervised learning. This course is one and half hours long, but you can learn the course at your convenience since the course is self-paced. You will be rewarded with the certificate after completing the course successfully.
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