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Udemy - Complete Linear Regression Analysis in Python 2024-11
- Enrolled students: 2
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Course content
Sections:
10
•
Activities:
0
•
Resources:
61
- 1 Welcome to the course
- 2 Course contents
- 4 This is a milestone
- test
- 5 Installing Python and Anaconda
- 6 Opening Jupyter Notebook
- 7 Introduction to Jupyter Notebook Part 1
- 8 Introduction to Jupyter Notebook Part 2
- 9 Arithmetic operators in Python
- 10 Strings in Python Part 1
- 11 Strings in Python Part 2
- 12 Lists Part 1
- 13 Lists Part 2
- 14 Tuples and Directories
- 15 Working with Numpy Library of Python
- 16 Working with Pandas Library of Python
- 17 Working with Seaborn Library of Python
- 19 Integrating ChatGPT with Jupyter notebook
- 20 Types of Data
- 21 Types of Statistics
- 22 Describing data Graphically
- 23 Measures of Centers
- 25 Measures of Dispersion
- 27 Introduction to Machine Learning
- 28 Building a Machine Learning Model
- 29 Gathering Business Knowledge
- 30 Data Exploration
- 31 The Dataset and the Data Dictionary
- 32 Importing Data in Python
- 34 Univariate analysis and EDD
- 35 EDD in Python
- 37 What is outlier treatment
- 38 Outlier Treatment in Python
- 40 Missing Value Imputation
- 41 Missing Value Imputation in Python
- 43 Seasonality in Data
- 44 Bivariate analysis and Variable transformation
- 45 Variable transformation and deletion in Python
- 47 Nonusable variables
- 48 Handling qualitative data by using dummy variables
- 49 Dummy variable creation in Python
- 51 Correlation Analysis
- 52 Correlation Analysis in Python
- 54 The Problem Statement
- 55 Basic Equations and Ordinary Least Squares OLS method
- 56 Assessing accuracy of predicted coefficients
- 57 Assessing Model Accuracy RSE and R squared
- 58 Simple Linear Regression in Python
- 60 Multiple Linear Regression
- 61 The F statistic
- 62 Interpreting results of Categorical variables
- 63 Multiple Linear Regression in Python
- 65 Testtrain split
- 66 Bias Variance tradeoff
- 68 Test train split in Python
- 69 Linear models other than OLS
- 70 Subset selection techniques
- 71 Shrinkage methods Ridge and Lasso
- 72 Ridge regression and Lasso in Python
- 73 Heteroscedasticity
- 77 The final milestone