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[ FreeCourseWeb ] Udemy - Machine Learning Basics- Building Regression Model in Python
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最近下载:
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文档列表
6. Linear Regression/18. 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/5. Assessing accuracy of predicted coefficients.mp4
109.5 MB
6. Linear Regression/10. Multiple Linear Regression in Python.mp4
92.4 MB
6. Linear Regression/16. Subset selection techniques.mp4
91.4 MB
5. Data Preprocessing/10. Outlier Treatment in Python.mp4
90.8 MB
2. Basics of Statistics/3. Describing data Graphically.mp4
86.2 MB
5. Data Preprocessing/23. Correlation Analysis.mp4
85.2 MB
3. Setting up Python and Jupyter Notebook/5. Strings in Python Python Basics.mp4
84.5 MB
6. Linear Regression/3. 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
3. Setting up Python and Jupyter Notebook/6. Lists, Tuples and Directories Python Basics.mp4
77.3 MB
3. 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
6. Linear Regression/8. The F - statistic.mp4
67.2 MB
6. Linear Regression/14. Test train split in Python.mp4
60.6 MB
3. Setting up Python and Jupyter Notebook/8. Working with Panda Library of Python.mp4
59.2 MB
3. 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
3. 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/6. Assessing Model Accuracy RSE and R squared.mp4
52.1 MB
6. Linear Regression/12. Test-train split.mp4
51.5 MB
3. 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
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
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/17. Shrinkage methods Ridge and Lasso.mp4
40.5 MB
5. Data Preprocessing/21. Dummy variable creation in Python.mp4
35.5 MB
5. Data Preprocessing/4. Importing Data in Python.mp4
34.0 MB
6. Linear Regression/13. Bias Variance trade-off.mp4
31.0 MB
5. Data Preprocessing/13. Missing Value Imputation in Python.mp4
30.0 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/9. Interpreting results of Categorical variables.mp4
28.4 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
6. Linear Regression/15. Linear models other than OLS.mp4
20.1 MB
3. Setting up Python and Jupyter Notebook/1. Installing Python and Anaconda.mp4
19.5 MB
1. Introduction/1. Welcome to the course!.mp4
17.1 MB
3. Setting up Python and Jupyter Notebook/4. Arithmetic operators in Python Python Basics.mp4
16.7 MB
2. Basics of Statistics/2. Types of Statistics.mp4
13.9 MB
6. Linear Regression/1. The Problem Statement.mp4
11.2 MB
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/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
16.7 kB
5. Data Preprocessing/16. Bi-variate analysis and Variable transformation.vtt
16.5 kB
3. Setting up Python and Jupyter Notebook/6. Lists, Tuples and Directories Python Basics.vtt
15.0 kB
3. Setting up Python and Jupyter Notebook/5. Strings in Python Python Basics.vtt
14.6 kB
6. Linear Regression/5. Assessing accuracy of predicted coefficients.vtt
14.3 kB
6. Linear Regression/20.1 Movie_collection_test.csv.csv
12.0 kB
2. Basics of Statistics/3. Describing data Graphically.vtt
11.6 kB
6. Linear Regression/16. Subset selection techniques.vtt
11.5 kB
5. Data Preprocessing/10. Outlier Treatment in Python.vtt
11.4 kB
6. Linear Regression/10. Multiple Linear Regression in Python.vtt
11.1 kB
3. Setting up Python and Jupyter Notebook/3. Introduction to Jupyter.vtt
11.0 kB
6. Linear Regression/3. Simple Linear Regression in Python.vtt
10.1 kB
5. Data Preprocessing/23. Correlation Analysis.vtt
10.0 kB
3. Setting up Python and Jupyter Notebook/7. Working with Numpy Library of Python.vtt
9.3 kB
5. Data Preprocessing/7. EDD in Python.vtt
9.2 kB
6. Linear Regression/2. Basic Equations and Ordinary Least Squares (OLS) method.vtt
8.9 kB
4. Introduction to Machine Learning/2. Building a Machine Learning Model.vtt
8.8 kB
3. Setting up Python and Jupyter Notebook/2. Opening Jupyter Notebook.vtt
8.2 kB
6. Linear Regression/8. The F - statistic.vtt
8.2 kB
3. Setting up Python and Jupyter Notebook/8. Working with Panda Library of Python.vtt
7.4 kB
6. Linear Regression/17. Shrinkage methods Ridge and Lasso.vtt
7.3 kB
6. Linear Regression/6. Assessing Model Accuracy RSE and R squared.vtt
7.2 kB
5. Data Preprocessing/3. The Dataset and the Data Dictionary.vtt
7.1 kB
5. Data Preprocessing/17. Variable transformation and deletion in Python.vtt
6.6 kB
2. Basics of Statistics/4. Measures of Centers.vtt
6.6 kB
5. Data Preprocessing/24. Correlation Analysis in Python.vtt
6.0 kB
6. Linear Regression/7. Multiple Linear Regression.vtt
5.2 kB
5. Data Preprocessing/4. Importing Data in Python.vtt
5.0 kB
5. Data Preprocessing/19. Non-usable variables.vtt
4.9 kB
5. Data Preprocessing/21. Dummy variable creation in Python.vtt
4.9 kB
2. Basics of Statistics/6. Measures of Dispersion.vtt
4.8 kB
6. Linear Regression/9. Interpreting results of Categorical variables.vtt
4.8 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/15. Linear models other than OLS.vtt
4.0 kB
5. Data Preprocessing/12. Missing Value Imputation.vtt
3.7 kB
5. Data Preprocessing/13. Missing Value Imputation in Python.vtt
3.7 kB
3. Setting up Python and Jupyter Notebook/4. Arithmetic operators in Python Python Basics.vtt
3.6 kB
5. Data Preprocessing/1. Gathering Business Knowledge.vtt
3.5 kB
5. Data Preprocessing/15. Seasonality in Data.vtt
3.4 kB
5. Data Preprocessing/2. Data Exploration.vtt
3.3 kB
5. Data Preprocessing/6. Univariate analysis and EDD.vtt
3.2 kB
2. Basics of Statistics/2. Types of Statistics.vtt
2.7 kB
1. Introduction/1. Welcome to the course!.vtt
2.7 kB
3. Setting up Python and Jupyter Notebook/1. Installing Python and Anaconda.vtt
2.3 kB
6. Linear Regression/21. Course Conclusion.html
1.7 kB
6. Linear Regression/1. The Problem Statement.vtt
1.5 kB
5. Data Preprocessing/5. Project exercise 1.html
431 Bytes
6. Linear Regression/19. Project Exercise 10.html
424 Bytes
2. Basics of Statistics/5. Practice Exercise 1.html
357 Bytes
6. Linear Regression/11. Project Exercise 9.html
327 Bytes
How to Support [ FreeCourseWeb.com ] for Free.txt
323 Bytes
6. Linear Regression/4. Project Exercise 8.html
322 Bytes
6. Linear Regression/20. Final Project Exercise.html
301 Bytes
2. 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
5. Data Preprocessing/22. Project Exercise 6.html
202 Bytes
5. Data Preprocessing/8. Project Exercise 2.html
177 Bytes
[ FreeCourseWeb.com ] Support Us.url
173 Bytes
4. Introduction to Machine Learning/3. Introduction to Machine learning quiz.html
166 Bytes
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