Data science masterclass with r! 4 projects+8 case studies
Indexed public MEGA.nz folder containing 478 files across 33 folders, with a total indexed size of 17.1 GB. Last scan: Sep 28, 2026.
Indexed contents
478 files in 33 folders
Files
- must read.txt
- 1. business case understanding.mp4
- 1. capstone project -introduction.mp4
- 1. logistics regression intuition.mp4
- 5. introduction to data scientist.mp4
- 9. data visualization - line chart.mp4
- 2. model deployment - pre requisite.mp4
- 3. introduction to machine learning.mp4
- 4. model deployment - azure ml demo.mp4
- 9. capstone project - decision tree.mp4
- 1. hierarchical clustering intuition.mp4
- 3. capstone project - lazy predictor.mp4
- 5. import text data in r study note.html
- 7. how to switch your career into ml.mp4
- 8. codes - telecom churn case study.html
- 8. data manipulation - pipe operator.vtt
- 1. data manipulation - apply function.mp4
- 1. introduction to business analytics.mp4
- 1. unsupervised learning introduction.mp4
- 3. model deployment - steps to follow.vtt
- 2. naive bayes - r code implementation.mp4
- 3. hierarchical clustering case study.mp4
- 4. capstone project - data preparation.mp4
- 2. random forest -r code implementation.mp4
- 3. codes - svm - r code implementation.html
- 4. all codes - hierarchical clustering.html
- 4. association rule mining - case study.mp4
- 5. all codes - association rule mining.html
- 1. association rule mining -introduction.mp4
- 2. capstone project - data understanding.mp4
- 3. decision tree - r code implementation.mp4
- 6. codes - matrix, array and data frame.html
- 4. data visualization - mfrow study note.html
- 6. capstone project - feature engineering.mp4
- 3. k-mean clustering r code implementation.mp4
- 7. capstone project - logistics regression.mp4
- 8. import excel, web data in r study note.html
- 1. dbscan clustering -intuition and r code.mp4
- 3. association rule mining - pre-processing.mp4
- 3. r conditional statement & loop study note.html
Showing a summary of 40 out of 478 files.
Folders
- 1. meet your instructor
- 2. introduction to data science
- 3. course curriculum overview
- 4. introduction to r
- 5. r programming
- 6. r data structure
- 7. import and export in r
- 8. data manipulation
- 9. data visualization
- data science masterclass with r! 4 projects+8 case studies
- 10. introduction to statistics
- 11. hypothesis testing -1
- 12. hypothesis testing in practice
- 13. machine learning toolbox
- 14. business use case understaing
- 15. data pre-processing
- 16. supervised learning regression
- 17. classification overview
- 18. logistic regression
- 19. k-nn
Showing a summary of 20 out of 33 folders.
Content summary
- Videos
- 140
- Archives
- 8
- Documents
- 49
- Others
- 254