FeaturedUdemy
Cluster Analysis in Python
4.8(1,002)65k studentsINTERMEDIATEEnglish
Korshub's take
The Korshub Take
Grouping similar items automatically—such as news articles or customer profiles—is a core application of unsupervised machine learning. This intermediate course provides a hands-on introduction to cluster analysis using SciPy in Python. Working with FIFA 18 player statistics, learners gain practical experience in data preprocessing and algorithm implementation to partition data effectively.
Who It's For
Intermediate Python developers and data analysts seeking to implement unsupervised learning techniques and cluster analysis in SciPy.
Key Takeaways
- Clustering Algorithms: Apply both hierarchical and k-means clustering techniques to discover natural groupings in datasets.
- Data Preprocessing: Learn essential data preparation steps required before feeding features into distance-based clustering algorithms.
- Visualization & Interpretation: Visualize cluster formations and analyze results using real-world sports analytics data from FIFA 18.
About this course
You have probably come across Google News, which automatically groups similar news articles under a topic. Have you ever wondered what process runs in the background to arrive at these groups? In this course, you will be introduced to unsupervised learning through clustering using the SciPy library in Python. This course covers pre-processing of data and application of hierarchical and k-means clustering. Through the course, you will explore player statistics from a popular football video game, FIFA 18. After completing the course, you will be able to quickly apply various clustering algorithms on data, visualize the clusters formed and analyze results.
Price
Free
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