本站已收录 番号和无损神作磁力链接/BT种子 

[FreeCourseSite.com] Udemy - Complete Linear Regression Analysis in Python

种子简介

种子名称: [FreeCourseSite.com] Udemy - Complete Linear Regression Analysis in Python
文件类型: 视频
文件数目: 55个文件
文件大小: 2.67 GB
收录时间: 2021-11-18 00:34
已经下载: 3
资源热度: 213
最近下载: 2024-11-27 09:23

下载BT种子文件

下载Torrent文件(.torrent) 立即下载

磁力链接下载

magnet:?xt=urn:btih:b9375ca495eea673e1807ae38fb7c41b62cb31c5&dn=[FreeCourseSite.com] Udemy - Complete Linear Regression Analysis in Python 复制链接到迅雷、QQ旋风进行下载,或者使用百度云离线下载。

喜欢这个种子的人也喜欢

种子包含的文件

[FreeCourseSite.com] Udemy - Complete Linear Regression Analysis in Python.torrent
  • 1. Introduction/1. Welcome to the course!.mp416.28MB
  • 1. Introduction/2. Course contents.mp447.85MB
  • 1. Introduction/4. This is a milestone!.mp420.66MB
  • 2. Setting up Python and Jupyter Notebook/1. Installing Python and Anaconda.mp418.61MB
  • 2. Setting up Python and Jupyter Notebook/2. Opening Jupyter Notebook.mp473.07MB
  • 2. Setting up Python and Jupyter Notebook/3. Introduction to Jupyter.mp451.3MB
  • 2. Setting up Python and Jupyter Notebook/4. Arithmetic operators in Python Python Basics.mp415.92MB
  • 2. Setting up Python and Jupyter Notebook/5. Strings in Python Python Basics.mp480.64MB
  • 2. Setting up Python and Jupyter Notebook/6. Lists, Tuples and Directories Python Basics.mp473.68MB
  • 2. Setting up Python and Jupyter Notebook/7. Working with Numpy Library of Python.mp454.12MB
  • 2. Setting up Python and Jupyter Notebook/8. Working with Pandas Library of Python.mp456.46MB
  • 2. Setting up Python and Jupyter Notebook/9. Working with Seaborn Library of Python.mp448.87MB
  • 3. Basics of Statistics/1. Types of Data.mp421.75MB
  • 3. Basics of Statistics/2. Types of Statistics.mp410.93MB
  • 3. Basics of Statistics/3. Describing data Graphically.mp465.38MB
  • 3. Basics of Statistics/4. Measures of Centers.mp438.55MB
  • 3. Basics of Statistics/6. Measures of Dispersion.mp422.86MB
  • 4. Introduction to Machine Learning/1. Introduction to Machine Learning.mp4123.89MB
  • 4. Introduction to Machine Learning/2. Building a Machine Learning Model.mp445.26MB
  • 5. Data Preprocessing/1. Gathering Business Knowledge.mp425.11MB
  • 5. Data Preprocessing/10. Outlier Treatment in Python.mp486.57MB
  • 5. Data Preprocessing/12. Missing Value Imputation.mp427.56MB
  • 5. Data Preprocessing/13. Missing Value Imputation in Python.mp428.59MB
  • 5. Data Preprocessing/15. Seasonality in Data.mp420.88MB
  • 5. Data Preprocessing/16. Bi-variate analysis and Variable transformation.mp4113.73MB
  • 5. Data Preprocessing/17. Variable transformation and deletion in Python.mp453.4MB
  • 5. Data Preprocessing/19. Non-usable variables.mp423.94MB
  • 5. Data Preprocessing/2. Data Exploration.mp423.41MB
  • 5. Data Preprocessing/20. Dummy variable creation Handling qualitative data.mp440.62MB
  • 5. Data Preprocessing/21. Dummy variable creation in Python.mp433.9MB
  • 5. Data Preprocessing/23. Correlation Analysis.mp481.31MB
  • 5. Data Preprocessing/24. Correlation Analysis in Python.mp468.02MB
  • 5. Data Preprocessing/3. The Dataset and the Data Dictionary.mp478.58MB
  • 5. Data Preprocessing/4. Importing Data in Python.mp432.46MB
  • 5. Data Preprocessing/6. Univariate analysis and EDD.mp427.29MB
  • 5. Data Preprocessing/7. EDD in Python.mp475.08MB
  • 5. Data Preprocessing/9. Outlier Treatment.mp427.78MB
  • 6. Linear Regression/1. The Problem Statement.mp410.69MB
  • 6. Linear Regression/10. Interpreting results of Categorical variables.mp427.13MB
  • 6. Linear Regression/11. Multiple Linear Regression in Python.mp488.13MB
  • 6. Linear Regression/14. Test-train split.mp449.13MB
  • 6. Linear Regression/15. Bias Variance trade-off.mp429.6MB
  • 6. Linear Regression/17. Test train split in Python.mp457.77MB
  • 6. Linear Regression/19. Linear models other than OLS.mp419.18MB
  • 6. Linear Regression/2. Basic Equations and Ordinary Least Squares (OLS) method.mp450.26MB
  • 6. Linear Regression/20. Subset selection techniques.mp487.15MB
  • 6. Linear Regression/21. Shrinkage methods Ridge and Lasso.mp438.64MB
  • 6. Linear Regression/22. Ridge regression and Lasso in Python.mp4156.63MB
  • 6. Linear Regression/23. Heteroscedasticity.mp417.73MB
  • 6. Linear Regression/3. Assessing accuracy of predicted coefficients.mp4104.42MB
  • 6. Linear Regression/4. Assessing Model Accuracy RSE and R squared.mp449.72MB
  • 6. Linear Regression/5. Simple Linear Regression in Python.mp478.64MB
  • 6. Linear Regression/7. Multiple Linear Regression.mp438.9MB
  • 6. Linear Regression/8. The F - statistic.mp464.12MB
  • 7. Bonus Section/1. The final milestone!.mp411.87MB