Coursera Machine Learning by Andrew Ng 14 Dimensionality Reduction Week 14 Principal Component Analysis Problem Formulation min mp4

Coursera Machine Learning by Andrew Ng
14 Dimensionality Reduction Week 14 Principal Component Analysis Problem Formulation min mp4

Name	[Coursera] Machine Learning by Andrew Ng	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	1.6 GB
Total Files	185
Last Seen	2025-04-14 23:28
Hash	48D1F81A7493A4B5440B09796F76B89EE160419F

/14. Dimensionality Reduction (Week 8)/14 - 3 - Principal Component Analysis Problem Formulation (9 min).mp4	11.0 MB
/14. Dimensionality Reduction (Week 8)/14 - 4 - Principal Component Analysis Algorithm (15 min).mp4	18.7 MB
/14. Dimensionality Reduction (Week 8)/14 - 2 - Motivation II- Visualization (6 min).mp4	6.6 MB
/14. Dimensionality Reduction (Week 8)/14 - 1 - Motivation I- Data Compression (10 min).mp4	15.0 MB
/14. Dimensionality Reduction (Week 8)/14 - 6 - Reconstruction from Compressed Representation (4 min).mp4	5.2 MB
/14. Dimensionality Reduction (Week 8)/14 - 7 - Advice for Applying PCA (13 min).mp4	15.4 MB
/14. Dimensionality Reduction (Week 8)/14 - 5 - Choosing the Number of Principal Components (11 min).mp4	12.4 MB
/15. Anomaly Detection (Week 9)/15 - 1 - Problem Motivation (8 min).mp4	8.8 MB
/15. Anomaly Detection (Week 9)/15 - 2 - Gaussian Distribution (10 min).mp4	12.3 MB
/16. Recommender Systems (Week 9)/16 - 1 - Problem Formulation (8 min).mp4	11.2 MB
/15. Anomaly Detection (Week 9)/15 - 5 - Anomaly Detection vs. Supervised Learning (8 min).mp4	9.7 MB
/15. Anomaly Detection (Week 9)/15 - 6 - Choosing What Features to Use (12 min).mp4	14.8 MB
/15. Anomaly Detection (Week 9)/15 - 7 - Multivariate Gaussian Distribution (Optional) (14 min).mp4	16.7 MB
/16. Recommender Systems (Week 9)/16 - 6 - Implementational Detail- Mean Normalization (9 min).mp4	10.2 MB
/06. Logistic Regression (Week 3)/6 - 2 - Hypothesis Representation (7 min).mp4	8.7 MB
Showing first 15 files of 185 total files