Descriptions
Data Science in Python: Unsupervised Learning, Learn foundational Python skills for unsupervised learning models, including clustering, anomaly detection, dimensionality reduction, and recommenders. This course covers the theory and practical implementation of unsupervised techniques, guiding you through real-world projects and hands-on exercises. By the end, you’ll be able to apply clustering algorithms, detect anomalies, reduce data dimensions, and build recommendation systems using Python.
What you’ll learn
- Understand the theory and intuition behind unsupervised learning models
- Implement clustering, anomaly detection, and dimensionality reduction in Python
- Build recommendation systems using unsupervised techniques
- Apply unsupervised learning to real-world datasets
Who this course is for
- Aspiring data scientists seeking hands-on experience with unsupervised learning in Python
- Analysts and professionals wanting to apply unsupervised techniques to real-world datasets
- Anyone looking to build practical skills in clustering, anomaly detection, and recommenders
Specificatoin of Data Science in Python: Unsupervised Learning
- Publisher : Maven Analytics
- Teacher : Alice Zhao
- Language : English
- Level : All Levels
- Duration : 28 hours and 0 minutes
Content of Data Science in Python: Unsupervised Learning
Requirements
- We strongly recommend taking our Data Prep & EDA course first
- Jupyter Notebooks (free download, we’ll walk through the install)
- Familiarity with base Python and Pandas is recommended, but not required
Pictures
Sample Clip
Video Player
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Installation Guide
Extract the files and watch with your favorite player
Subtitle : English
Quality: 1080p
Download Links
Downloadly
Rapidgator
Password file(s): www.downloadly.ir
File size
2.62 GB
