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| File Name: | Machine Learning with Python: k-Means Clustering |
| Content Source: | https://www.linkedin.com/learning/machine-learning-with-python-k-means-clustering |
| Genre / Category: | Programming |
| File Size : | 127MB |
| Publisher: | |
| Updated and Published: | May 24, 2022 |
Clustering—an unsupervised machine learning approach used to group data based on similarity—is used for work in network analysis, market segmentation, search results grouping, medical imaging, and anomaly detection. K-means clustering is one of the most popular and easy to use clustering algorithms. In this course, Fred Nwanganga gives you an introductory look at k-means clustering—how it works, what it’s good for, when you should use it, how to choose the right number of clusters, its strengths and weaknesses, and more. Fred provides hands-on guidance on how to collect, explore, and transform data in preparation for segmenting data using k-means clustering, and gives a step-by-step guide on how to build such a model in Python.
DOWNLOAD LINK: Machine Learning with Python: k-Means Clustering
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