Advanced Statistical Methods in Python – 365 Data Science

Advanced Statistical Methods in Python – 365 Data Science Free Download.

Advanced Statistical Methods in Python – 365 Data Science Description

1. Linear regression:
Correlation vs Regression – 365 Data Science
Decomposition of Variability – 365 Data Science
First Regression in Python – 365 Data Science
Geometrical Representation of the Linear Regression Model – 365 Data Science
How to Interpret the Regression Table – 365 Data Science
Introduction to Regression Analysis – 365 Data Science
Python Packages Installation – 365 Data Science
R-Squared – 365 Data Science
The Linear Regression Model – 365 Data Science
Using Seaborn for Graphs – 365 Data Science
Welcome to Advanced Statistics! – 365 Data Science
What is the OLS- – 365 Data Science

2. Multiple Linear Regression:
A1- Linearity – 365 Data Science
A2- No Endogeneity – 365 Data Science
A3- Normality and Homoscedasticity – 365 Data Science
A4- No Autocorrelation – 365 Data Science
A5- No Multicollinearity – 365 Data Science
Adjusted R-Squared – 365 Data Science
Dealing with Categorical Data – Dummy Variables – 365 Data Science
Making Predictions with the Linear Regression – 365 Data Science
Multiple Linear Regression – 365 Data Science
OLS Assumptions – 365 Data Science
Test for Significance of the Model (F-Test) – 365 Data Science

CISCO CYBEROPS: MANAGING POLICIES AND PROCEDURES

3. Linear Regression with sklearn:
Adjusted R-Squared – 365 Data Science
Creating a Summary Table with the p-values – 365 Data Science
Feature Scaling – 365 Data Science
Feature Selection through p-values (F-regression) – 365 Data Science
Feature Selection through Standardization – 365 Data Science
Game Plan for sklearn – 365 Data Science
Making Predictions with Standardized Coefficients – 365 Data Science
Multiple Linear Regression with sklearn – 365 Data Science
Simple Linear Regression with sklearn – 365 Data Science
Simple Linear Regression with sklearn – Summary Table – 365 Data Science
Training and Testing – 365 Data Science
Underfitting and Overfitting – 365 Data Science
What is sklearn- – 365 Data Science

4. Linear Regression – Practical Example:
Practical Example (Part 1) – 365 Data Science
Practical Example (Part 2) – 365 Data Science
Practical Example (Part 3) – 365 Data Science
Practical Example (Part 4) – 365 Data Science
Practical Example (Part 5) – 365 Data Science

5. Logistic Regression:
A Simple Example in Python – 365 Data Science
An Invaluable Coding Tip – 365 Data Science
Binary Predictors in a Logistic Regression – 365 Data Science
Building a Logistic Regression – 365 Data Science
Calculating the Accuracy of the Model – 365 Data Science
Introduction to Cluster Analysis – 365 Data Science
Introduction to Logistic Regression – 365 Data Science
Logistic vs Logit Function – 365 Data Science
Underfitting and Overfitting – 365 Data Science
Understanding Logistic Regression Tables – 365 Data Science
What do the Odds Actually Mean – 365 Data Science

6. Cluster Analysis (Basics and Prerequisites):
Difference between Classification and Clustering – 365 Data Science
Introduction to Cluster Analysis – 365 Data Science
Math Prerequisites – 365 Data Science
Some Examples of Clusters – 365 Data Science

7. K-Means Clustering:
A Simple Example of Clustering – 365 Data Science
Clustering Categorical Data – 365 Data Science
How is Clustering Useful- – 365 Data Science
How to Choose the Number of Clusters – 365 Data Science
K-Means Clustering – 365 Data Science
Market Segmentation with Cluster Analysis (Part 1) – 365 Data Science
Market Segmentation with Cluster Analysis (Part 2) – 365 Data Science
Pros and Cons of K-Means Clustering – 365 Data Science
Relationship between Clustering and Regression – 365 Data Science
To Standardize or to not Standardize – 365 Data Science

8. Other Types of Clustering:
Dendrogram – 365 Data Science
Heatmaps – 365 Data Science
Types of Clustering – 365 Data Science

Advanced Statistical Methods in Python – 365 Data Science Free Download

OneDrive

Password: freetutsdownload.com

HOW TO DOWNLOAD COURSE

Content From: https://365datascience.com/

Copyright Disclaimer:

This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us (in author info), we’ll remove relevant links or contents immediately.

Leave a Comment