Learn · Biological data analysis and visualization with R

Lecture 40 of 42Week 8 :

Lecture 40 : Random Forests

Prof. Riddhiman Dhar · IIT Kharagpur

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Biological data analysis and visualization with R, IIT Kharagpur (at NPTEL)
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All the lectures

  1. Lecture 01 : Introduction Video
  2. Lecture 02 : Setting up R Video
  3. Lecture 03 : Basic functions in R Video
  4. Lecture 04 : Basic data structures in R Video
  5. Lecture 05 : Data structures and File I/O Video
  6. Lecture 06 : Basic statistical tests with R Video
  7. Lecture 07 : Correlation analysis Video
  8. Lecture 08 : Analysis of variance (ANOVA) Video
  9. Lecture 09 : Basic data visualization techniques Video
  10. Lecture 10 : Data visualization Video
  11. Lecture 11 : Visualization with vioplot and ggplot2 Video
  12. Lecture 12 : R packages for plotting and data organization Video
  13. Lecture 13 : Data transformation in R Video
  14. Lecture 14 : Bioconductor packages Video
  15. Lecture 15 : Flow cytometry data analysis in R/Bioconductor Video
  16. Lecture 16 : Gene expression analysis and co-expression network Video
  17. Lecture 17 : WGCNA package and Data Download Video
  18. Lecture 18 : WGCNA hands-on: Data preprocessing Video
  19. Lecture 19 : WGCNA hands-on: Soft-threshold Video
  20. Lecture 20 : WGCNA: Module gene expression Video
  21. Lecture 21 : Introduction to ChIP-seq Video
  22. Lecture 22 : ChIP-seq data analysis Video
  23. Lecture 23 : ChIP-seq data analysis: Peak calling Video
  24. Lecture 24 : Peak calling and Visualization Video
  25. Lecture 25 : ChIP-seq data analysis: bigWig/bw files Video
  26. Lecture 26 : Regression models on Biological data Video
  27. Lecture 27 : Predictive models with linear regression Video
  28. Lecture 28 : Multicollinearity Video
  29. Lecture 29 : Lasso regression Video
  30. Lecture 30 : Non-linear regression Video
  31. Lecture 31: Dimensionality reduction Video
  32. Lecture 32 : Principal Component Analysis (PCA) Video
  33. Lecture 33: PCA analysis hands-on Video
  34. Lecture 34: PCA analysis using ‘PCAtools’ Video
  35. Lecture 35 : UMAP analysis Video
  36. Lecture 36 : Classification of biological samples Video
  37. Lecture 37 : Penalized and Stepwise Logistic regression Video
  38. Lecture 38 : Decision trees Video
  39. Lecture 39 : Classification and Regression trees Video
  40. Lecture 40 : Random Forests Video
  41. Live Session 10-03-2025 Video
  42. Live Session 16-04-2025 Video