Unsupervised Machine Learning with K-means
Learn Unsupervised Machine Learning with K Means technique to analyse and cluster unlabelled dataset
Skills you’ll Learn
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.
Check out our PG Course in Machine learning Today.
Course Outline
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.
This section discusses Supervised and Unsupervised Machine Learning methods to accomplish various tasks.