[FreeCourseSite.com] Udemy - Linear Regression and Logistic Regression in Python

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[FreeCourseSite.com] Udemy - Linear Regression and Logistic Regression in Python

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种子哈希：46c902f596edf163cc210076ee251de3617c8eaf
文件大小： 2.49G
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收录时间：2022-02-20
最近下载：2024-12-11

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文件列表

  • 4. Data Preprocessing before building Linear Regression Model/12. Bi-variate analysis and Variable transformation.mp4 105.3 MB
  • 5. Building the Linear Regression Model/3. Assessing accuracy of predicted coefficients.mp4 96.6 MB
  • 6. Logistic Regression Data Preprocessing/1. The Dataset and the Data Dictionary.mp4 83.0 MB
  • 6. Logistic Regression Data Preprocessing/3. EDD in Python.mp4 81.3 MB
  • 4. Data Preprocessing before building Linear Regression Model/17. Correlation Analysis.mp4 75.1 MB
  • 4. Data Preprocessing before building Linear Regression Model/8. Outlier Treatment in Python.mp4 73.7 MB
  • 5. Building the Linear Regression Model/9. Multiple Linear Regression in Python.mp4 73.1 MB
  • 4. Data Preprocessing before building Linear Regression Model/3. The Dataset and the Data Dictionary.mp4 72.7 MB
  • 3. Basics of Statistics/3. Describing data Graphically.mp4 68.5 MB
  • 2. Setting up Python and Python Crash Course/3. Opening Jupyter Notebook.mp4 68.4 MB
  • 2. Setting up Python and Python Crash Course/6. Strings in Python Python Basics.mp4 67.6 MB
  • 5. Building the Linear Regression Model/5. Simple Linear Regression in Python.mp4 66.5 MB
  • 4. Data Preprocessing before building Linear Regression Model/6. EDD in Python.mp4 64.8 MB
  • 2. Setting up Python and Python Crash Course/7. Lists, Tuples and Directories Python Basics.mp4 63.3 MB
  • 5. Building the Linear Regression Model/7. The F - statistic.mp4 58.8 MB
  • 4. Data Preprocessing before building Linear Regression Model/18. Correlation Analysis in Python.mp4 58.0 MB
  • 7. Building a Logistic Regression Model/8. Creating Confusion Matrix in Python.mp4 53.8 MB
  • 7. Building a Logistic Regression Model/3. Training a Simple Logistic Model in Python.mp4 50.2 MB
  • 6. Logistic Regression Data Preprocessing/4. Outlier Treatment in Python.mp4 49.6 MB
  • 2. Setting up Python and Python Crash Course/9. Working with Pandas Library of Python.mp4 49.2 MB
  • 5. Building the Linear Regression Model/13. Test train split in Python.mp4 47.1 MB
  • 4. Data Preprocessing before building Linear Regression Model/13. Variable transformation and deletion in Python.mp4 46.2 MB
  • 2. Setting up Python and Python Crash Course/8. Working with Numpy Library of Python.mp4 46.0 MB
  • 5. Building the Linear Regression Model/4. Assessing Model Accuracy RSE and R squared.mp4 45.7 MB
  • 5. Building the Linear Regression Model/2. Basic Equations and Ordinary Least Squares (OLS) method.mp4 45.5 MB
  • 5. Building the Linear Regression Model/10. Test-train split.mp4 43.9 MB
  • 2. Setting up Python and Python Crash Course/4. Introduction to Jupyter.mp4 42.9 MB
  • 2. Setting up Python and Python Crash Course/10. Working with Seaborn Library of Python.mp4 42.3 MB
  • 8. Test-Train Split/1. Test-Train Split.mp4 41.2 MB
  • 3. Basics of Statistics/4. Measures of Centers.mp4 40.5 MB
  • 4. Data Preprocessing before building Linear Regression Model/15. Dummy variable creation Handling qualitative data.mp4 38.6 MB
  • 7. Building a Logistic Regression Model/9. Evaluating performance of model.mp4 36.9 MB
  • 5. Building the Linear Regression Model/6. Multiple Linear Regression.mp4 36.0 MB
  • 8. Test-Train Split/2. Test-Train Split in Python.mp4 34.7 MB
  • 7. Building a Logistic Regression Model/2. Logistic Regression.mp4 34.5 MB
  • 6. Logistic Regression Data Preprocessing/6. Variable transformation and Deletion in Python.mp4 30.7 MB
  • 4. Data Preprocessing before building Linear Regression Model/4. Importing Data in Python.mp4 29.2 MB
  • 7. Building a Logistic Regression Model/4. Result of Simple Logistic Regression.mp4 28.2 MB
  • 4. Data Preprocessing before building Linear Regression Model/16. Dummy variable creation in Python.mp4 27.8 MB
  • 6. Logistic Regression Data Preprocessing/7. Dummy variable creation in Python.mp4 27.7 MB
  • 7. Building a Logistic Regression Model/6. Training multiple predictor Logistic model in Python.mp4 27.5 MB
  • 5. Building the Linear Regression Model/11. Bias Variance trade-off.mp4 26.3 MB
  • 4. Data Preprocessing before building Linear Regression Model/9. Missing Value Imputation.mp4 26.2 MB
  • 1. Introduction/1. Introduction.mp4 25.9 MB
  • 4. Data Preprocessing before building Linear Regression Model/7. Outlier Treatment.mp4 25.7 MB
  • 4. Data Preprocessing before building Linear Regression Model/5. Univariate analysis and EDD.mp4 25.4 MB
  • 4. Data Preprocessing before building Linear Regression Model/10. Missing Value Imputation in Python.mp4 24.5 MB
  • 3. Basics of Statistics/5. Measures of Dispersion.mp4 24.0 MB
  • 6. Logistic Regression Data Preprocessing/5. Missing Value Imputation in Python.mp4 23.7 MB
  • 5. Building the Linear Regression Model/8. Interpreting results of Categorical variables.mp4 23.6 MB
  • 4. Data Preprocessing before building Linear Regression Model/1. Gathering Business Knowledge.mp4 23.4 MB
  • 6. Logistic Regression Data Preprocessing/2. Data Import in Python.mp4 23.1 MB
  • 3. Basics of Statistics/1. Types of Data.mp4 22.8 MB
  • 7. Building a Logistic Regression Model/7. Confusion Matrix.mp4 22.1 MB
  • 2. Setting up Python and Python Crash Course/2. This is a milestone!.mp4 21.6 MB
  • 4. Data Preprocessing before building Linear Regression Model/2. Data Exploration.mp4 21.5 MB
  • 4. Data Preprocessing before building Linear Regression Model/14. Non-usable variables.mp4 21.2 MB
  • 4. Data Preprocessing before building Linear Regression Model/11. Seasonality in Data.mp4 17.9 MB
  • 7. Building a Logistic Regression Model/1. Why can't we use Linear Regression.mp4 17.8 MB
  • 2. Setting up Python and Python Crash Course/1. Installing Python and Anaconda.mp4 17.1 MB
  • 2. Setting up Python and Python Crash Course/5. Arithmetic operators in Python Python Basics.mp4 13.4 MB
  • 9. Bonus Section/1. The final milestone!.mp4 12.4 MB
  • 3. Basics of Statistics/2. Types of Statistics.mp4 11.5 MB
  • 5. Building the Linear Regression Model/1. The Problem Statement.mp4 9.8 MB
  • 7. Building a Logistic Regression Model/10. Evaluating model performance in Python.mp4 9.4 MB
  • 7. Building a Logistic Regression Model/5. Logistic with multiple predictors.mp4 8.9 MB
  • 2. Setting up Python and Python Crash Course/7. Lists, Tuples and Directories Python Basics.srt 20.6 kB
  • 4. Data Preprocessing before building Linear Regression Model/12. Bi-variate analysis and Variable transformation.srt 19.8 kB
  • 2. Setting up Python and Python Crash Course/6. Strings in Python Python Basics.srt 18.4 kB
  • 6. Logistic Regression Data Preprocessing/3. EDD in Python.srt 18.2 kB
  • 5. Building the Linear Regression Model/3. Assessing accuracy of predicted coefficients.srt 17.8 kB
  • 5. Building the Linear Regression Model/9. Multiple Linear Regression in Python.srt 14.6 kB
  • 4. Data Preprocessing before building Linear Regression Model/8. Outlier Treatment in Python.srt 14.5 kB
  • 2. Setting up Python and Python Crash Course/4. Introduction to Jupyter.srt 13.5 kB
  • 5. Building the Linear Regression Model/5. Simple Linear Regression in Python.srt 13.4 kB
  • 3. Basics of Statistics/3. Describing data Graphically.srt 13.1 kB
  • 4. Data Preprocessing before building Linear Regression Model/17. Correlation Analysis.srt 12.2 kB
  • 2. Setting up Python and Python Crash Course/8. Working with Numpy Library of Python.srt 12.1 kB
  • 4. Data Preprocessing before building Linear Regression Model/6. EDD in Python.srt 11.9 kB
  • 5. Building the Linear Regression Model/10. Test-train split.srt 11.1 kB
  • 7. Building a Logistic Regression Model/8. Creating Confusion Matrix in Python.srt 11.1 kB
  • 7. Building a Logistic Regression Model/3. Training a Simple Logistic Model in Python.srt 10.9 kB
  • 8. Test-Train Split/1. Test-Train Split.srt 10.8 kB
  • 5. Building the Linear Regression Model/2. Basic Equations and Ordinary Least Squares (OLS) method.srt 10.7 kB
  • 2. Setting up Python and Python Crash Course/9. Working with Pandas Library of Python.srt 10.4 kB
  • 2. Setting up Python and Python Crash Course/3. Opening Jupyter Notebook.srt 10.1 kB
  • 5. Building the Linear Regression Model/7. The F - statistic.srt 9.9 kB
  • 6. Logistic Regression Data Preprocessing/4. Outlier Treatment in Python.srt 9.8 kB
  • 7. Building a Logistic Regression Model/9. Evaluating performance of model.srt 9.6 kB
  • 6. Logistic Regression Data Preprocessing/1. The Dataset and the Data Dictionary.srt 9.5 kB
  • 4. Data Preprocessing before building Linear Regression Model/13. Variable transformation and deletion in Python.srt 9.2 kB
  • 4. Data Preprocessing before building Linear Regression Model/3. The Dataset and the Data Dictionary.srt 9.0 kB
  • 5. Building the Linear Regression Model/13. Test train split in Python.srt 8.9 kB
  • 7. Building a Logistic Regression Model/2. Logistic Regression.srt 8.8 kB
  • 2. Setting up Python and Python Crash Course/10. Working with Seaborn Library of Python.srt 8.8 kB
  • 5. Building the Linear Regression Model/4. Assessing Model Accuracy RSE and R squared.srt 8.6 kB
  • 3. Basics of Statistics/4. Measures of Centers.srt 8.1 kB
  • 8. Test-Train Split/2. Test-Train Split in Python.srt 7.6 kB
  • 4. Data Preprocessing before building Linear Regression Model/18. Correlation Analysis in Python.srt 7.1 kB
  • 5. Building the Linear Regression Model/11. Bias Variance trade-off.srt 7.1 kB
  • 4. Data Preprocessing before building Linear Regression Model/4. Importing Data in Python.srt 6.6 kB
  • 5. Building the Linear Regression Model/6. Multiple Linear Regression.srt 6.5 kB
  • 4. Data Preprocessing before building Linear Regression Model/16. Dummy variable creation in Python.srt 6.4 kB
  • 6. Logistic Regression Data Preprocessing/7. Dummy variable creation in Python.srt 6.3 kB
  • 4. Data Preprocessing before building Linear Regression Model/14. Non-usable variables.srt 6.2 kB
  • 7. Building a Logistic Regression Model/6. Training multiple predictor Logistic model in Python.srt 6.2 kB
  • 5. Building the Linear Regression Model/8. Interpreting results of Categorical variables.srt 6.1 kB
  • 7. Building a Logistic Regression Model/4. Result of Simple Logistic Regression.srt 6.0 kB
  • 4. Data Preprocessing before building Linear Regression Model/15. Dummy variable creation Handling qualitative data.srt 5.9 kB
  • 7. Building a Logistic Regression Model/1. Why can't we use Linear Regression.srt 5.6 kB
  • 6. Logistic Regression Data Preprocessing/2. Data Import in Python.srt 5.4 kB
  • 3. Basics of Statistics/5. Measures of Dispersion.srt 5.4 kB
  • 4. Data Preprocessing before building Linear Regression Model/7. Outlier Treatment.srt 5.2 kB
  • 3. Basics of Statistics/1. Types of Data.srt 5.2 kB
  • 7. Building a Logistic Regression Model/7. Confusion Matrix.srt 5.0 kB
  • 6. Logistic Regression Data Preprocessing/5. Missing Value Imputation in Python.srt 4.9 kB
  • 4. Data Preprocessing before building Linear Regression Model/10. Missing Value Imputation in Python.srt 4.9 kB
  • 2. Setting up Python and Python Crash Course/5. Arithmetic operators in Python Python Basics.srt 4.5 kB
  • 6. Logistic Regression Data Preprocessing/6. Variable transformation and Deletion in Python.srt 4.4 kB
  • 4. Data Preprocessing before building Linear Regression Model/9. Missing Value Imputation.srt 4.3 kB
  • 4. Data Preprocessing before building Linear Regression Model/1. Gathering Business Knowledge.srt 4.2 kB
  • 4. Data Preprocessing before building Linear Regression Model/5. Univariate analysis and EDD.srt 4.1 kB
  • 4. Data Preprocessing before building Linear Regression Model/11. Seasonality in Data.srt 4.1 kB
  • 4. Data Preprocessing before building Linear Regression Model/2. Data Exploration.srt 4.0 kB
  • 2. Setting up Python and Python Crash Course/2. This is a milestone!.srt 3.9 kB
  • 1. Introduction/1. Introduction.srt 3.8 kB
  • 3. Basics of Statistics/2. Types of Statistics.srt 3.2 kB
  • 7. Building a Logistic Regression Model/5. Logistic with multiple predictors.srt 3.0 kB
  • 7. Building a Logistic Regression Model/10. Evaluating model performance in Python.srt 2.7 kB
  • 2. Setting up Python and Python Crash Course/1. Installing Python and Anaconda.srt 2.7 kB
  • 9. Bonus Section/1. The final milestone!.srt 1.8 kB
  • 5. Building the Linear Regression Model/1. The Problem Statement.srt 1.7 kB
  • 9. Bonus Section/2. Congratulations & About your certificate.html 1.6 kB
  • 5. Building the Linear Regression Model/12. More about test-train split.html 559 Bytes
  • 1. Introduction/2. Course Resources.html 388 Bytes
  • 4. Data Preprocessing before building Linear Regression Model/19. Quiz.html 212 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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