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[DesireCourse.Net] Udemy - Machine Learning for Beginners Linear Regression model in R
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[DesireCourse.Net] Udemy - Machine Learning for Beginners Linear Regression model in R
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最近下载:
2024-11-11
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文件列表
7. Regression models other than OLS/6. 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/16. Test-Train Split in R.mp4
95.5 MB
7. Regression models other than OLS/2. 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
7. Regression models other than OLS/3. Subset selection in R.mp4
80.3 MB
6. Linear Regression Model/11. 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
71.1 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
52.1 MB
6. Linear Regression Model/14. 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/3. 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
7. Regression models other than OLS/5. 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/15. 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
24.5 MB
5. Data Preprocessing/15. Seasonality in Data.mp4
21.9 MB
7. Regression models other than OLS/1. Linear models other than OLS.mp4
20.1 MB
7. Regression models other than OLS/7. Heteroscedasticity.mp4
18.6 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
1. Introduction/2.1 Files_linear_r.zip
9.0 MB
4. Introduction to Machine Learning/1.1 Lecture_machineLearning.pdf
1.0 MB
4. Introduction to Machine Learning/2.1 Lecture_machineLearning.pdf
1.0 MB
1. Introduction/3.1 00_Introduction_01.pdf
810.5 kB
2. Basics of Statistics/5.1 Exercise 1.pdf
567.1 kB
2. Basics of Statistics/7.1 Exercise 2.pdf
481.2 kB
5. Data Preprocessing/16.1 04_07_Variable_Transformation.pdf
433.0 kB
5. Data Preprocessing/15.1 04_07_PDE_Seasonality.pdf
372.8 kB
5. Data Preprocessing/9.1 04_06_PDE_Outlier_Treatment.pdf
363.7 kB
5. Data Preprocessing/6.1 03_04_PDE_Univariate_Analysis_Uni.pdf
341.4 kB
6. Linear Regression Model/3.1 05_03_Simple_lin_reg_Accuracy.pdf
340.7 kB
6. Linear Regression Model/4.1 05_03_Simple_lin_reg_Accuracy.pdf
340.7 kB
5. Data Preprocessing/3.2 03_03_PDE_Raw_Data_Analysis_Uni.pdf
339.9 kB
6. Linear Regression Model/8.1 05_05_F_stat.pdf
336.4 kB
5. Data Preprocessing/12.1 04_05_PDE_Missing_value.pdf
333.5 kB
5. Data Preprocessing/2.1 03_02_PDE_Data_exploration.pdf
330.7 kB
2. Basics of Statistics/3.1 01_03_Lecture_DataSummaryandGraph.pdf
325.5 kB
2. Basics of Statistics/4.1 01_04_Lecture_Centers.pdf
320.5 kB
6. Linear Regression Model/2.1 05_02_Simple_lin_reg.pdf
291.6 kB
5. Data Preprocessing/23.1 04_10_Correlation.pdf
263.1 kB
6. Linear Regression Model/1.1 05_01_Intro.pdf
245.1 kB
6. Linear Regression Model/14.1 05_12_Test_Train.pdf
244.5 kB
6. Linear Regression Model/7.1 05_04_Multiple_lin_reg.pdf
225.1 kB
2. Basics of Statistics/6.1 01_05_Lecture_Dispersion.pdf
215.6 kB
6. Linear Regression Model/15.1 05_13_Bias_Var_tradeoff.pdf
207.2 kB
7. Regression models other than OLS/2.1 05_10_Subset_Selection.pdf
203.3 kB
7. Regression models other than OLS/5.1 05_11_Shrinkage_methods.pdf
192.6 kB
2. Basics of Statistics/1.1 01_01_Lecture_TypesOfData.pdf
182.0 kB
2. Basics of Statistics/2.1 01_02_Lecture_TypesOfStatistics.pdf
175.9 kB
5. Data Preprocessing/20.1 04_11_Dummy_Var.pdf
166.9 kB
7. Regression models other than OLS/1.1 05_09_Other_lin_model.pdf
160.3 kB
6. Linear Regression Model/9.1 05_06_Cat_var.pdf
159.2 kB
5. Data Preprocessing/1.1 03_01_PDE_Business_knowledge.pdf
157.6 kB
5. Data Preprocessing/19.1 04_08_PDE_Non_Usable_var.pdf
141.7 kB
3. Getting started with R and R studio/6.1 Customer.csv
65.6 kB
5. Data Preprocessing/3.1 House_Price.csv
54.8 kB
5. Data Preprocessing/4.2 House_Price.csv
54.8 kB
5. Data Preprocessing/5.1 Movie_collection_train.csv
44.4 kB
4. Introduction to Machine Learning/1. Introduction to Machine Learning.srt
23.8 kB
5. Data Preprocessing/16. Bi-variate Analysis and Variable Transformation.srt
18.7 kB
3. Getting started with R and R studio/7. Creating Barplots in R.srt
18.6 kB
6. Linear Regression Model/3. Assessing Accuracy of predicted coefficients.srt
16.2 kB
3. Getting started with R and R studio/3. Packages in R.srt
14.7 kB
3. Getting started with R and R studio/2. Basics of R and R studio.srt
14.6 kB
2. Basics of Statistics/3. Describing the data graphically.srt
13.2 kB
7. Regression models other than OLS/2. Subset Selection techniques.srt
13.1 kB
4. Introduction to Machine Learning/2. Building a Machine Learning model.srt
13.1 kB
8. Conclusion/1.1 Movie_collection_test.csv
12.0 kB
5. Data Preprocessing/7. EDD in R.srt
11.8 kB
7. Regression models other than OLS/6. Ridge regression and Lasso in R.srt
11.7 kB
5. Data Preprocessing/23. Correlation Matrix and cause-effect relationship.srt
11.3 kB
1. Introduction/3. Course contents.srt
10.4 kB
6. Linear Regression Model/14. Test-Train split.srt
10.3 kB
6. Linear Regression Model/2. Basic equations and Ordinary Least Squared (OLS) method.srt
10.1 kB
5. Data Preprocessing/24. Correlation Matrix in R.srt
9.3 kB
5. Data Preprocessing/17. Variable transformation in R.srt
9.3 kB
6. Linear Regression Model/8. The F - statistic.srt
9.2 kB
6. Linear Regression Model/16. Test-Train Split in R.srt
8.6 kB
3. Getting started with R and R studio/6. Inputting data part 3 Importing from CSV or Text files.srt
8.5 kB
6. Linear Regression Model/11. Multiple Linear Regression in R.srt
8.3 kB
7. Regression models other than OLS/5. Shrinkage methods - Ridge Regression and The Lasso.srt
8.2 kB
6. Linear Regression Model/4. Assessing Model Accuracy - RSE and R squared.srt
8.2 kB
6. Linear Regression Model/5. Simple Linear Regression in R.srt
8.2 kB
5. Data Preprocessing/3. The Data and the Data Dictionary.srt
8.0 kB
7. Regression models other than OLS/3. Subset selection in R.srt
7.8 kB
3. Getting started with R and R studio/8. Creating Histograms in R.srt
7.7 kB
3. Getting started with R and R studio/1. Installing R and R studio.srt
7.5 kB
2. Basics of Statistics/4. Measures of Centers.srt
7.4 kB
6. Linear Regression Model/15. Bias Variance trade-off.srt
6.6 kB
6. Linear Regression Model/7. Multiple Linear Regression.srt
5.9 kB
3. Getting started with R and R studio/4. Inputting data part 1 Inbuilt datasets of R.srt
5.6 kB
5. Data Preprocessing/19. Non Usable Variables.srt
5.5 kB
2. Basics of Statistics/6. Measures of Dispersion.srt
5.5 kB
6. Linear Regression Model/9. Interpreting result for categorical Variable.srt
5.4 kB
5. Data Preprocessing/21. Dummy variable creation in R.srt
5.3 kB
2. Basics of Statistics/1. Types of Data.srt
5.0 kB
5. Data Preprocessing/20. Dummy variable creation Handling qualitative data.srt
5.0 kB
5. Data Preprocessing/9. Outlier Treatment.srt
4.6 kB
7. Regression models other than OLS/1. Linear models other than OLS.srt
4.5 kB
5. Data Preprocessing/10. Outlier Treatment in R.srt
4.4 kB
5. Data Preprocessing/12. Missing Value imputation.srt
4.2 kB
5. Data Preprocessing/1. Gathering Business Knowledge.srt
4.0 kB
5. Data Preprocessing/15. Seasonality in Data.srt
3.9 kB
3. Getting started with R and R studio/5. Inputting data part 2 Manual data entry.srt
3.7 kB
5. Data Preprocessing/2. Data Exploration.srt
3.7 kB
5. Data Preprocessing/13. Missing Value imputation in R.srt
3.5 kB
5. Data Preprocessing/6. Univariate Analysis and EDD.srt
3.5 kB
1. Introduction/1. Welcome to the course!.srt
3.5 kB
2. Basics of Statistics/2. Types of Statistics.srt
3.1 kB
7. Regression models other than OLS/7. Heteroscedasticity.srt
2.7 kB
5. Data Preprocessing/4. Importing the dataset into R.srt
2.7 kB
8. Conclusion/3. Bonus Lecture.html
1.7 kB
6. Linear Regression Model/1. The problem statement.srt
1.7 kB
5. Data Preprocessing/4.1 R_Linear.zip
1.2 kB
8. Conclusion/2. Course Conclusion.html
946 Bytes
5. Data Preprocessing/5. Project Exercise 1.html
447 Bytes
7. Regression models other than OLS/8. Project Exercise 11.html
398 Bytes
2. Basics of Statistics/5. Practice Exercise 1.html
354 Bytes
8. Conclusion/1. Final Project Exercise.html
329 Bytes
6. Linear Regression Model/13. Project Exercise 9.html
328 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
7. Regression models other than OLS/4. 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
167 Bytes
6. Linear Regression Model/10. Quiz.html
167 Bytes
6. Linear Regression Model/12. Quiz.html
167 Bytes
6. Linear Regression Model/17. Quiz.html
167 Bytes
1. Introduction/2. Course Resources.html
117 Bytes
0. Websites you may like/[FreeCourseWorld.Com].url
54 Bytes
[FreeCourseWorld.Com].url
54 Bytes
0. Websites you may like/[DesireCourse.Net].url
51 Bytes
[DesireCourse.Net].url
51 Bytes
0. Websites you may like/[CourseClub.Me].url
48 Bytes
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