UDEMY Linear Regression and Logistic Regression using R Studio BOOKWARE-iLEARN

By Pacman On May 31, 2022

UDEMY Linear Regression and Logistic Regression using R Studio BOOKWARE-iLEARN | Apps-Tutorials | MP4 | 2.54 GiB

993 kb/s 1280×720 | AAC 128 kb/s 2 CH

File List (Click to Show)

25M	1. Introduction.mp4
39M	10. Basics of R and R studio.mp4
83M	11. Packages in R.mp4
41M	12. Inputting data part 1 Inbuilt datasets of R.mp4
26M	13. Inputting data part 2 Manual data entry.mp4
61M	14. Inputting data part 3 Importing from CSV or Text files.mp4
97M	15. Creating Barplots in R.mp4
43M	16. Creating Histograms in R.mp4
15M	17. Gathering Business Knowledge.mp4
21M	18. Data Exploration.mp4
70M	19. The Data and the Data Dictionary.mp4
14M	20. Importing the dataset into R.mp4
25M	21. Univariate Analysis and EDD.mp4
97M	22. EDD in R.mp4
25M	23. Outlier Treatment.mp4
31M	24. Outlier Treatment in R.mp4
25M	25. Missing Value imputation.mp4
26M	26. Missing Value imputation in R.mp4
18M	27. Seasonality in Data.mp4
101M	28. Bi-variate Analysis and Variable Transformation.mp4
56M	29. Variable transformation in R.mp4
22M	3. Types of Data.mp4
21M	30. Non Usable Variables.mp4
37M	31. Dummy variable creation Handling qualitative data.mp4
45M	32. Dummy variable creation in R.mp4
72M	33. Correlation Matrix and cause-effect relationship.mp4
84M	34. Correlation Matrix in R.mp4
9.4M	35. The problem statement.mp4
44M	36. Basic equations and Ordinary Least Squared (OLS) method.mp4
93M	37. Assessing Accuracy of predicted coefficients.mp4
44M	38. Assessing Model Accuracy - RSE and R squared.mp4
41M	39. Simple Linear Regression in R.mp4
21M	4. This is a milestone!.mp4
35M	40. Multiple Linear Regression.mp4
57M	41. The F - statistic.mp4
23M	42. Interpreting result for categorical Variable.mp4
63M	43. Multiple Linear Regression in R.mp4
42M	44. Test-Train split.mp4
26M	45. Bias Variance trade-off.mp4
76M	47. Test-Train Split in R.mp4
80M	48. The Data and the Data Dictionary.mp4
14M	49. Importing the dataset into R.mp4
11M	5. Types of Statistics.mp4
67M	50. EDD in R.mp4
26M	51. Outlier Treatment in R.mp4
20M	52. Missing Value imputation in R.mp4
39M	53. Variable transformation in R.mp4
45M	54. Dummy variable creation in R.mp4
17M	55. Why can't we use Linear Regression.mp4
33M	56. Logistic Regression.mp4
26M	57. Training a Simple Logistic model in R.mp4
27M	58. Results of Simple Logistic Regression.mp4
8.6M	59. Logistic with multiple predictors.mp4
66M	6. Describing the data graphically.mp4
16M	60. Training multiple predictor Logistic model in R.mp4
22M	61. Confusion Matrix.mp4
36M	62. Evaluating Model performance.mp4
56M	63. Predicting probabilities, assigning classes and making Confusion Matrix.mp4
40M	64. Test-Train Split.mp4
75M	65. Test-Train Split in R.mp4
12M	66. The final milestone!.mp4
39M	7. Measures of Centers.mp4
23M	8. Measures of Dispersion.mp4
36M	9. Installing R and R studio.mp4
2.6G	total

File: 1. Introduction.mp4
Size: 25640728 bytes (24.45 MiB), duration: 00:03:26, avg.bitrate: 996 kb/s
Audio: aac, 44100 Hz, stereo (und)
Video: h264, yuv420p, 1280x720, 30.00 fps(r) => 1279x720 (und)

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Keywords: UDEMY, Linear, Regression, and, Logistic, Regression, using, Studio, BOOKWARE, iLEARN

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