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[DesireCourse.Com] Udemy - Machine Learning Basics Building a Regression model in R
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[DesireCourse.Com] Udemy - Machine Learning Basics Building a Regression model in R
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文件列表
6. Linear Regression Model/20. Ridge regression and Lasso in R.mp4
130.3 MB
4. Introduction to Machine Learning/1. Introduction to Machine Learning.mp4
129.9 MB
3. Getting started with R and R studio/7. Creating Barplots in R.mp4
123.3 MB
5. Data Preprocessing/16. Bi-variate Analysis and Variable Transformation.mp4
119.3 MB
5. Data Preprocessing/7. EDD in R.mp4
117.7 MB
6. Linear Regression Model/3. Assessing Accuracy of predicted coefficients.mp4
109.5 MB
3. Getting started with R and R studio/3. Packages in R.mp4
103.5 MB
5. Data Preprocessing/24. Correlation Matrix in R.mp4
99.7 MB
6. Linear Regression Model/14. Test-Train Split in R.mp4
95.5 MB
6. Linear Regression Model/16. Subset Selection techniques.mp4
91.3 MB
2. Basics of Statistics/3. Describing the data graphically.mp4
86.2 MB
5. Data Preprocessing/23. Correlation Matrix and cause-effect relationship.mp4
85.2 MB
5. Data Preprocessing/3. The Data and the Data Dictionary.mp4
82.4 MB
6. Linear Regression Model/17. Subset selection in R.mp4
80.3 MB
6. Linear Regression Model/10. Multiple Linear Regression in R.mp4
76.7 MB
3. Getting started with R and R studio/6. Inputting data part 3 Importing from CSV or Text files.mp4
72.5 MB
5. Data Preprocessing/17. Variable transformation in R.mp4
71.2 MB
6. Linear Regression Model/8. The F - statistic.mp4
67.3 MB
5. Data Preprocessing/21. Dummy variable creation in R.mp4
54.8 MB
3. Getting started with R and R studio/8. Creating Histograms in R.mp4
54.0 MB
6. Linear Regression Model/5. Simple Linear Regression in R.mp4
53.1 MB
6. Linear Regression Model/2. Basic equations and Ordinary Least Squared (OLS) method.mp4
52.7 MB
6. Linear Regression Model/4. Assessing Model Accuracy - RSE and R squared.mp4
52.2 MB
6. Linear Regression Model/12. Test-Train split.mp4
51.5 MB
3. Getting started with R and R studio/2. Basics of R and R studio.mp4
50.5 MB
1. Introduction/2. Course contents.mp4
49.3 MB
3. Getting started with R and R studio/4. Inputting data part 1 Inbuilt datasets of R.mp4
48.4 MB
2. Basics of Statistics/4. Measures of Centers.mp4
47.9 MB
4. Introduction to Machine Learning/2. Building a Machine Learning model.mp4
47.5 MB
3. Getting started with R and R studio/1. Installing R and R studio.mp4
42.8 MB
5. Data Preprocessing/20. Dummy variable creation Handling qualitative data.mp4
42.6 MB
6. Linear Regression Model/7. Multiple Linear Regression.mp4
40.8 MB
6. Linear Regression Model/19. Shrinkage methods - Ridge Regression and The Lasso.mp4
40.5 MB
5. Data Preprocessing/10. Outlier Treatment in R.mp4
39.8 MB
5. Data Preprocessing/13. Missing Value imputation in R.mp4
33.3 MB
3. Getting started with R and R studio/5. Inputting data part 2 Manual data entry.mp4
32.4 MB
6. Linear Regression Model/13. Bias Variance trade-off.mp4
31.0 MB
2. Basics of Statistics/6. Measures of Dispersion.mp4
29.8 MB
5. Data Preprocessing/9. Outlier Treatment.mp4
29.1 MB
5. Data Preprocessing/12. Missing Value imputation.mp4
28.9 MB
5. Data Preprocessing/6. Univariate Analysis and EDD.mp4
28.6 MB
6. Linear Regression Model/9. Interpreting result for categorical Variable.mp4
28.5 MB
2. Basics of Statistics/1. Types of Data.mp4
27.1 MB
5. Data Preprocessing/1. Gathering Business Knowledge.mp4
26.3 MB
5. Data Preprocessing/19. Non Usable Variables.mp4
25.1 MB
5. Data Preprocessing/2. Data Exploration.mp4
24.6 MB
5. Data Preprocessing/15. Seasonality in Data.mp4
21.9 MB
6. Linear Regression Model/15. Linear models other than OLS.mp4
20.1 MB
5. Data Preprocessing/4. Importing the dataset into R.mp4
16.8 MB
1. Introduction/1. Welcome to the course!.mp4
16.2 MB
2. Basics of Statistics/2. Types of Statistics.mp4
13.9 MB
6. Linear Regression Model/1. The problem statement.mp4
11.2 MB
5. Data Preprocessing/19. Non Usable Variables.vtt
2.1 MB
4. Introduction to Machine Learning/1.1 Lecture_machineLearning.pdf.pdf
1.0 MB
4. Introduction to Machine Learning/2.1 Lecture_machineLearning.pdf.pdf
1.0 MB
1. Introduction/2.1 00_Introduction_01.pdf.pdf
810.5 kB
2. Basics of Statistics/5.1 Exercise 1.pdf.pdf
567.1 kB
2. Basics of Statistics/7.1 Exercise 2.pdf.pdf
481.2 kB
5. Data Preprocessing/16.1 04_07_Variable_Transformation.pdf.pdf
433.0 kB
5. Data Preprocessing/15.1 04_07_PDE_Seasonality.pdf.pdf
372.8 kB
5. Data Preprocessing/9.1 04_06_PDE_Outlier_Treatment.pdf.pdf
363.7 kB
5. Data Preprocessing/6.1 03_04_PDE_Univariate_Analysis_Uni.pdf.pdf
341.4 kB
6. Linear Regression Model/3.1 05_03_Simple_lin_reg_Accuracy.pdf.pdf
340.7 kB
6. Linear Regression Model/4.1 05_03_Simple_lin_reg_Accuracy.pdf.pdf
340.7 kB
5. Data Preprocessing/3.2 03_03_PDE_Raw_Data_Analysis_Uni.pdf.pdf
339.9 kB
6. Linear Regression Model/8.1 05_05_F_stat.pdf.pdf
336.4 kB
5. Data Preprocessing/2.1 03_02_PDE_Data_exploration.pdf.pdf
330.7 kB
2. Basics of Statistics/3.1 01_03_Lecture_DataSummaryandGraph.pdf.pdf
325.5 kB
5. Data Preprocessing/12.1 04_05_PDE_Missing_value.pdf.pdf
323.3 kB
2. Basics of Statistics/4.1 01_04_Lecture_Centers.pdf.pdf
320.5 kB
6. Linear Regression Model/2.1 05_02_Simple_lin_reg.pdf.pdf
291.6 kB
5. Data Preprocessing/23.1 04_10_Correlation.pdf.pdf
263.1 kB
6. Linear Regression Model/1.1 05_01_Intro.pdf.pdf
245.1 kB
6. Linear Regression Model/12.1 05_12_Test_Train.pdf.pdf
244.5 kB
6. Linear Regression Model/7.1 05_04_Multiple_lin_reg.pdf.pdf
225.1 kB
2. Basics of Statistics/6.1 01_05_Lecture_Dispersion.pdf.pdf
215.6 kB
6. Linear Regression Model/13.1 05_13_Bias_Var_tradeoff.pdf.pdf
207.2 kB
6. Linear Regression Model/16.1 05_10_Subset_Selection.pdf.pdf
203.3 kB
6. Linear Regression Model/19.1 05_11_Shrinkage_methods.pdf.pdf
192.6 kB
2. Basics of Statistics/1.1 01_01_Lecture_TypesOfData.pdf.pdf
182.0 kB
2. Basics of Statistics/2.1 01_02_Lecture_TypesOfStatistics.pdf.pdf
175.9 kB
5. Data Preprocessing/20.1 04_11_Dummy_Var.pdf.pdf
166.9 kB
6. Linear Regression Model/15.1 05_09_Other_lin_model.pdf.pdf
160.3 kB
6. Linear Regression Model/9.1 05_06_Cat_var.pdf.pdf
159.2 kB
5. Data Preprocessing/1.1 03_01_PDE_Business_knowledge.pdf.pdf
157.6 kB
5. Data Preprocessing/19.1 04_08_PDE_Non_Usable_var.pdf.pdf
141.7 kB
5. Data Preprocessing/3.1 House_Price.csv.csv
54.8 kB
5. Data Preprocessing/4.1 House_Price.csv.csv
54.8 kB
5. Data Preprocessing/5.1 Movie_collection_train.csv.csv
44.4 kB
4. Introduction to Machine Learning/1. Introduction to Machine Learning.vtt
21.5 kB
3. Getting started with R and R studio/7. Creating Barplots in R.vtt
16.7 kB
5. Data Preprocessing/16. Bi-variate Analysis and Variable Transformation.vtt
16.5 kB
6. Linear Regression Model/3. Assessing Accuracy of predicted coefficients.vtt
14.3 kB
3. Getting started with R and R studio/3. Packages in R.vtt
13.2 kB
3. Getting started with R and R studio/2. Basics of R and R studio.vtt
13.1 kB
6. Linear Regression Model/22.1 Movie_collection_test.csv.csv
12.0 kB
4. Introduction to Machine Learning/2. Building a Machine Learning model.vtt
11.8 kB
2. Basics of Statistics/3. Describing the data graphically.vtt
11.6 kB
6. Linear Regression Model/16. Subset Selection techniques.vtt
11.5 kB
5. Data Preprocessing/7. EDD in R.vtt
10.3 kB
6. Linear Regression Model/20. Ridge regression and Lasso in R.vtt
10.1 kB
5. Data Preprocessing/23. Correlation Matrix and cause-effect relationship.vtt
10.0 kB
1. Introduction/2. Course contents.vtt
9.6 kB
6. Linear Regression Model/12. Test-Train split.vtt
9.2 kB
6. Linear Regression Model/2. Basic equations and Ordinary Least Squared (OLS) method.vtt
8.9 kB
5. Data Preprocessing/24. Correlation Matrix in R.vtt
8.3 kB
6. Linear Regression Model/8. The F - statistic.vtt
8.2 kB
5. Data Preprocessing/17. Variable transformation in R.vtt
8.2 kB
3. Getting started with R and R studio/6. Inputting data part 3 Importing from CSV or Text files.vtt
7.7 kB
6. Linear Regression Model/14. Test-Train Split in R.vtt
7.5 kB
6. Linear Regression Model/19. Shrinkage methods - Ridge Regression and The Lasso.vtt
7.3 kB
6. Linear Regression Model/10. Multiple Linear Regression in R.vtt
7.3 kB
6. Linear Regression Model/5. Simple Linear Regression in R.vtt
7.3 kB
6. Linear Regression Model/4. Assessing Model Accuracy - RSE and R squared.vtt
7.2 kB
5. Data Preprocessing/3. The Data and the Data Dictionary.vtt
7.1 kB
3. Getting started with R and R studio/8. Creating Histograms in R.vtt
6.9 kB
6. Linear Regression Model/17. Subset selection in R.vtt
6.8 kB
3. Getting started with R and R studio/1. Installing R and R studio.vtt
6.8 kB
2. Basics of Statistics/4. Measures of Centers.vtt
6.6 kB
6. Linear Regression Model/13. Bias Variance trade-off.vtt
5.8 kB
6. Linear Regression Model/7. Multiple Linear Regression.vtt
5.2 kB
3. Getting started with R and R studio/4. Inputting data part 1 Inbuilt datasets of R.vtt
5.1 kB
2. Basics of Statistics/6. Measures of Dispersion.vtt
4.8 kB
6. Linear Regression Model/9. Interpreting result for categorical Variable.vtt
4.8 kB
5. Data Preprocessing/21. Dummy variable creation in R.vtt
4.6 kB
2. Basics of Statistics/1. Types of Data.vtt
4.4 kB
5. Data Preprocessing/20. Dummy variable creation Handling qualitative data.vtt
4.4 kB
5. Data Preprocessing/9. Outlier Treatment.vtt
4.1 kB
6. Linear Regression Model/15. Linear models other than OLS.vtt
4.0 kB
5. Data Preprocessing/10. Outlier Treatment in R.vtt
3.9 kB
5. Data Preprocessing/12. Missing Value imputation.vtt
3.7 kB
5. Data Preprocessing/1. Gathering Business Knowledge.vtt
3.5 kB
5. Data Preprocessing/15. Seasonality in Data.vtt
3.4 kB
3. Getting started with R and R studio/5. Inputting data part 2 Manual data entry.vtt
3.3 kB
5. Data Preprocessing/2. Data Exploration.vtt
3.3 kB
1. Introduction/1. Welcome to the course!.vtt
3.2 kB
5. Data Preprocessing/6. Univariate Analysis and EDD.vtt
3.2 kB
5. Data Preprocessing/13. Missing Value imputation in R.vtt
3.1 kB
2. Basics of Statistics/2. Types of Statistics.vtt
2.7 kB
5. Data Preprocessing/4. Importing the dataset into R.vtt
2.3 kB
6. Linear Regression Model/23. Course Conclusion.html
1.7 kB
6. Linear Regression Model/1. The problem statement.vtt
1.5 kB
5. Data Preprocessing/5. Project Exercise 1.html
431 Bytes
6. Linear Regression Model/21. Project Exercise 11.html
398 Bytes
2. Basics of Statistics/5. Practice Exercise 1.html
354 Bytes
6. Linear Regression Model/22. Final Project Exercise.html
329 Bytes
6. Linear Regression Model/11. Project Exercise 9.html
327 Bytes
6. Linear Regression Model/6. Project Exercise 8.html
322 Bytes
2. Basics of Statistics/7. Practice Exercise 2.html
295 Bytes
5. Data Preprocessing/25. Project Exercise 7.html
288 Bytes
5. Data Preprocessing/18. Project Exercise 5.html
286 Bytes
5. Data Preprocessing/14. Project Exercise 4.html
238 Bytes
5. Data Preprocessing/11. Project Exercise 3.html
233 Bytes
5. Data Preprocessing/22. Project Exercise 6.html
202 Bytes
6. Linear Regression Model/18. Project Exercise 10.html
199 Bytes
5. Data Preprocessing/8. Project Exercise 2.html
177 Bytes
4. Introduction to Machine Learning/3. Introduction to Machine learning quiz.html
163 Bytes
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