Engineering and Technology
This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.
In the field of machine learning, there is often a need to identify patterns in data without the intention of making predictions. This approach is referred to as unsupervised learning. One practical application of unsupervised learning involves categorizing consumers based on their demographics and purchasing behavior to effectively implement targeted marketing strategies. Another scenario involves understanding the underlying factors that contribute to variations in crime rates among different cities. This course offers a fundamental introduction to clustering and dimensionality reduction techniques in R, specifically from a machine learning standpoint. The objective is to equip you with the necessary skills to efficiently derive meaningful insights from data. By mastering these techniques, you will be able to navigate from raw data to valuable knowledge in a streamlined manner.
by DataCamp
This course provides an intro to clustering and dimensionality reduction in R from a machine learnin...
by DataCamp
Learn how to apply advanced dimensionality techniques such as t-SNE and GLRM.
by DataCamp
Sharpen your knowledge and prepare for your next interview by practicing Python machine learning int...
by DataCamp
Understand the fundamentals of Machine Learning and how it's applied in the business world.
by DataCamp
In this course, you will be introduced to unsupervised learning through techniques such as hierarchi...
by DataCamp
Learn how to detect fraud using Python.