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[FreeCourseSite.com] Udemy - Complete Linear Regression Analysis in Python
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[FreeCourseSite.com] Udemy - Complete Linear Regression Analysis in Python
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2022-01-09
最近下载:
2024-11-13
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文件列表
6. Linear Regression/22. Ridge regression and Lasso in Python.mp4
164.2 MB
4. Introduction to Machine Learning/1. Introduction to Machine Learning.mp4
129.9 MB
5. Data Preprocessing/16. Bi-variate analysis and Variable transformation.mp4
119.3 MB
6. Linear Regression/3. Assessing accuracy of predicted coefficients.mp4
109.5 MB
6. Linear Regression/11. Multiple Linear Regression in Python.mp4
92.4 MB
6. Linear Regression/20. Subset selection techniques.mp4
91.4 MB
5. Data Preprocessing/10. Outlier Treatment in Python.mp4
90.8 MB
5. Data Preprocessing/23. Correlation Analysis.mp4
85.3 MB
2. Setting up Python and Jupyter Notebook/5. Strings in Python Python Basics.mp4
84.6 MB
6. Linear Regression/5. Simple Linear Regression in Python.mp4
82.5 MB
5. Data Preprocessing/3. The Dataset and the Data Dictionary.mp4
82.4 MB
5. Data Preprocessing/7. EDD in Python.mp4
78.7 MB
2. Setting up Python and Jupyter Notebook/6. Lists, Tuples and Directories Python Basics.mp4
77.3 MB
2. Setting up Python and Jupyter Notebook/2. Opening Jupyter Notebook.mp4
76.6 MB
5. Data Preprocessing/24. Correlation Analysis in Python.mp4
71.3 MB
3. Basics of Statistics/3. Describing data Graphically.mp4
68.6 MB
6. Linear Regression/8. The F - statistic.mp4
67.2 MB
6. Linear Regression/17. Test train split in Python.mp4
60.6 MB
2. Setting up Python and Jupyter Notebook/8. Working with Pandas Library of Python.mp4
59.2 MB
2. Setting up Python and Jupyter Notebook/7. Working with Numpy Library of Python.mp4
56.8 MB
5. Data Preprocessing/17. Variable transformation and deletion in Python.mp4
56.0 MB
2. Setting up Python and Jupyter Notebook/3. Introduction to Jupyter.mp4
53.8 MB
6. Linear Regression/2. Basic Equations and Ordinary Least Squares (OLS) method.mp4
52.7 MB
6. Linear Regression/4. Assessing Model Accuracy RSE and R squared.mp4
52.1 MB
6. Linear Regression/14. Test-train split.mp4
51.5 MB
2. Setting up Python and Jupyter Notebook/9. Working with Seaborn Library of Python.mp4
51.2 MB
1. Introduction/2. Course contents.mp4
50.2 MB
4. Introduction to Machine Learning/2. Building a Machine Learning Model.mp4
47.5 MB
5. Data Preprocessing/20. Dummy variable creation Handling qualitative data.mp4
42.6 MB
6. Linear Regression/7. Multiple Linear Regression.mp4
40.8 MB
6. Linear Regression/21. Shrinkage methods Ridge and Lasso.mp4
40.5 MB
3. Basics of Statistics/4. Measures of Centers.mp4
40.4 MB
5. Data Preprocessing/21. Dummy variable creation in Python.mp4
35.6 MB
5. Data Preprocessing/4. Importing Data in Python.mp4
34.0 MB
6. Linear Regression/15. Bias Variance trade-off.mp4
31.0 MB
5. Data Preprocessing/13. Missing Value Imputation in Python.mp4
30.0 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/10. Interpreting results of Categorical variables.mp4
28.4 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
3. Basics of Statistics/6. Measures of Dispersion.mp4
24.0 MB
3. Basics of Statistics/1. Types of Data.mp4
22.8 MB
5. Data Preprocessing/15. Seasonality in Data.mp4
21.9 MB
1. Introduction/4. This is a milestone!.mp4
21.7 MB
6. Linear Regression/19. Linear models other than OLS.mp4
20.1 MB
2. Setting up Python and Jupyter Notebook/1. Installing Python and Anaconda.mp4
19.5 MB
6. Linear Regression/23. Heteroscedasticity.mp4
18.6 MB
1. Introduction/1. Welcome to the course!.mp4
17.1 MB
2. Setting up Python and Jupyter Notebook/4. Arithmetic operators in Python Python Basics.mp4
16.7 MB
7. Bonus Section/1. The final milestone!.mp4
12.5 MB
3. Basics of Statistics/2. Types of Statistics.mp4
11.5 MB
6. Linear Regression/1. The Problem Statement.mp4
11.2 MB
4. Introduction to Machine Learning/2.1 Lecture_machineLearning.pdf
1.0 MB
4. Introduction to Machine Learning/1.1 Lecture_machineLearning.pdf
1.0 MB
1. Introduction/2.1 00_Introduction_01.pdf
820.7 kB
3. Basics of Statistics/5.1 Exercise 1.pdf
567.1 kB
3. 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/3.1 05_03_Simple_lin_reg_Accuracy.pdf
340.7 kB
6. Linear Regression/4.1 05_03_Simple_lin_reg_Accuracy.pdf
340.7 kB
5. Data Preprocessing/3.1 03_03_PDE_Raw_Data_Analysis_Uni.pdf
339.9 kB
6. Linear Regression/8.1 05_05_F_stat.pdf
336.4 kB
3. Basics of Statistics/4.1 01_04_Lecture_Centers.pdf
330.7 kB
5. Data Preprocessing/2.1 03_02_PDE_Data_exploration.pdf
330.7 kB
3. Basics of Statistics/3.1 01_03_Lecture_DataSummaryandGraph.pdf
325.5 kB
5. Data Preprocessing/12.1 04_05_PDE_Missing_value.pdf
323.3 kB
6. Linear Regression/2.1 05_02_Simple_lin_reg.pdf
291.6 kB
5. Data Preprocessing/23.1 04_10_Correlation.pdf
273.3 kB
6. Linear Regression/1.1 05_01_Intro.pdf
245.1 kB
6. Linear Regression/14.1 05_12_Test_Train.pdf
244.5 kB
6. Linear Regression/7.1 05_04_Multiple_lin_reg.pdf
225.1 kB
6. Linear Regression/15.1 05_13_Bias_Var_tradeoff.pdf
217.5 kB
6. Linear Regression/20.1 05_10_Subset_Selection.pdf
213.5 kB
6. Linear Regression/21.1 05_11_Shrinkage_methods.pdf
192.6 kB
3. Basics of Statistics/1.1 01_01_Lecture_TypesOfData.pdf
182.0 kB
3. 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
6. Linear Regression/19.1 05_09_Other_lin_model.pdf
160.3 kB
6. Linear Regression/10.1 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
2. Setting up Python and Jupyter Notebook/8.1 Customer.csv
65.6 kB
5. Data Preprocessing/3.2 House_Price.csv
54.8 kB
5. Data Preprocessing/4.1 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
19.0 kB
5. Data Preprocessing/16. Bi-variate analysis and Variable transformation.srt
18.9 kB
6. Linear Regression/22. Ridge regression and Lasso in Python.srt
18.8 kB
2. Setting up Python and Jupyter Notebook/6. Lists, Tuples and Directories Python Basics.srt
18.1 kB
2. Setting up Python and Jupyter Notebook/5. Strings in Python Python Basics.srt
17.4 kB
6. Linear Regression/3. Assessing accuracy of predicted coefficients.srt
16.5 kB
6. Linear Regression/20. Subset selection techniques.srt
13.2 kB
6. Linear Regression/11. Multiple Linear Regression in Python.srt
13.1 kB
3. Basics of Statistics/3. Describing data Graphically.srt
13.1 kB
5. Data Preprocessing/10. Outlier Treatment in Python.srt
13.0 kB
2. Setting up Python and Jupyter Notebook/3. Introduction to Jupyter.srt
12.7 kB
6. Linear Regression/25.1 Movie_collection_test.csv
12.0 kB
5. Data Preprocessing/23. Correlation Analysis.srt
12.0 kB
6. Linear Regression/5. Simple Linear Regression in Python.srt
12.0 kB
2. Setting up Python and Jupyter Notebook/7. Working with Numpy Library of Python.srt
11.1 kB
5. Data Preprocessing/7. EDD in Python.srt
10.6 kB
6. Linear Regression/14. Test-train split.srt
10.6 kB
4. Introduction to Machine Learning/2. Building a Machine Learning Model.srt
10.1 kB
6. Linear Regression/2. Basic Equations and Ordinary Least Squares (OLS) method.srt
10.0 kB
1. Introduction/2. Course contents.srt
9.7 kB
6. Linear Regression/8. The F - statistic.srt
9.3 kB
2. Setting up Python and Jupyter Notebook/2. Opening Jupyter Notebook.srt
9.1 kB
2. Setting up Python and Jupyter Notebook/8. Working with Pandas Library of Python.srt
9.0 kB
6. Linear Regression/21. Shrinkage methods Ridge and Lasso.srt
8.7 kB
5. Data Preprocessing/3. The Dataset and the Data Dictionary.srt
8.3 kB
3. Basics of Statistics/4. Measures of Centers.srt
8.1 kB
6. Linear Regression/4. Assessing Model Accuracy RSE and R squared.srt
8.0 kB
6. Linear Regression/17. Test train split in Python.srt
8.0 kB
5. Data Preprocessing/17. Variable transformation and deletion in Python.srt
7.7 kB
2. Setting up Python and Jupyter Notebook/9. Working with Seaborn Library of Python.srt
7.5 kB
5. Data Preprocessing/24. Correlation Analysis in Python.srt
6.9 kB
6. Linear Regression/15. Bias Variance trade-off.srt
6.7 kB
6. Linear Regression/7. Multiple Linear Regression.srt
6.0 kB
5. Data Preprocessing/19. Non-usable variables.srt
5.8 kB
5. Data Preprocessing/4. Importing Data in Python.srt
5.8 kB
5. Data Preprocessing/20. Dummy variable creation Handling qualitative data.srt
5.5 kB
5. Data Preprocessing/21. Dummy variable creation in Python.srt
5.5 kB
6. Linear Regression/10. Interpreting results of Categorical variables.srt
5.5 kB
3. Basics of Statistics/6. Measures of Dispersion.srt
5.4 kB
3. Basics of Statistics/1. Types of Data.srt
5.2 kB
5. Data Preprocessing/9. Outlier Treatment.srt
4.9 kB
6. Linear Regression/19. Linear models other than OLS.srt
4.5 kB
2. Setting up Python and Jupyter Notebook/4. Arithmetic operators in Python Python Basics.srt
4.3 kB
5. Data Preprocessing/13. Missing Value Imputation in Python.srt
4.2 kB
5. Data Preprocessing/12. Missing Value Imputation.srt
4.2 kB
5. Data Preprocessing/1. Gathering Business Knowledge.srt
4.1 kB
5. Data Preprocessing/15. Seasonality in Data.srt
3.9 kB
1. Introduction/4. This is a milestone!.srt
3.9 kB
5. Data Preprocessing/6. Univariate analysis and EDD.srt
3.8 kB
5. Data Preprocessing/2. Data Exploration.srt
3.8 kB
1. Introduction/1. Welcome to the course!.srt
3.6 kB
3. Basics of Statistics/2. Types of Statistics.srt
3.2 kB
6. Linear Regression/23. Heteroscedasticity.srt
2.8 kB
2. Setting up Python and Jupyter Notebook/1. Installing Python and Anaconda.srt
2.6 kB
7. Bonus Section/2. Congratulations & About your certificate.html
1.9 kB
7. Bonus Section/1. The final milestone!.srt
1.8 kB
6. Linear Regression/1. The Problem Statement.srt
1.7 kB
6. Linear Regression/16. More about test-train split.html
559 Bytes
5. Data Preprocessing/5. Project exercise 1.html
431 Bytes
6. Linear Regression/24. Project Exercise 10.html
424 Bytes
3. Basics of Statistics/5. Practice Exercise 1.html
357 Bytes
1. Introduction/3. Course Resources.html
336 Bytes
6. Linear Regression/13. Project Exercise 9.html
327 Bytes
6. Linear Regression/6. Project Exercise 8.html
322 Bytes
6. Linear Regression/25. Final Project Exercise.html
301 Bytes
3. Basics of Statistics/7. Practice Exercise 2.html
300 Bytes
5. Data Preprocessing/25. Project Exercise 7.html
288 Bytes
5. Data Preprocessing/18. Project Exercise 5.html
285 Bytes
5. Data Preprocessing/14. Project Exercise 4.html
238 Bytes
5. Data Preprocessing/11. Project Exercise 3.html
233 Bytes
4. Introduction to Machine Learning/3. Introduction to Machine learning quiz.html
210 Bytes
5. Data Preprocessing/26. Quiz.html
210 Bytes
6. Linear Regression/12. Quiz.html
210 Bytes
6. Linear Regression/18. Quiz.html
210 Bytes
6. Linear Regression/9. Quiz.html
210 Bytes
5. Data Preprocessing/22. Project Exercise 6.html
202 Bytes
5. Data Preprocessing/8. Project Exercise 2.html
177 Bytes
0. Websites you may like/[FCS Forum].url
133 Bytes
0. Websites you may like/[FreeCourseSite.com].url
127 Bytes
0. Websites you may like/[CourseClub.ME].url
122 Bytes
0. Websites you may like/[GigaCourse.Com].url
49 Bytes
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