Supervised Machine Learning Complete Masterclass [2023]

سرفصل های دوره

1. Introduction

1. Introduction

2. Machine Learning, Artificial Intelligence, and Supervised Machine Learning

1. Machine Learning Introduction

2. Table of Content

3. How AI Work

4. Types of AI

5. Application of AI

6. Domains of AI

7. What is Machine Learning

8. How ML Works

9. Classification of ML

10. Trends in ML

11. Supervised ML

12. Supervised ML Algorithms 1

13. SML Algorithms 2

3. Supervised Machine Learning Explained

1. Classification of SML

2. What is Regression

3. Example of Classification

4. Types of Classification

5. Binary Classification

6. Multi-Class Classification

7. Multi-Labeled Classification

8. Regression Example

9. Simple Linear Regression

10. Multi-Linear Regression

11. Polynomial Regression

12. Graph of SLR

13. Graph of Polynomial Regression

14. Regression Code in Python

15. Data Preprocessing

16. Model Development

17. SSRSST

18. Use of SciKit in Programming

4. Regression Analysis for SML

1. Example Simple Linear Regression

2. Collection of Data

3. Plotting SLR

4. Preprocessing of Data

5. Splitting Data

6. SLR Score

7. PR in Python

8. Poly-Scatter Plot

5. KNN-Model for SML

1. K-Nearest Neighbor

2. KNN Classification

3. Label Encoder

4. KNN Model Development

5. SK Learn

6. Importing Data Set

7. Selection of Model

6. Decision Tree

1. What is a Decision Tree

2. How to Code Decision Tree

3. Decision Tree Regression

7. Data Visualization for SML

1. What is Data Visualization

2. Import Matplotlib

3. Plot in Matplotlib

4. Simple Plotting

5. Axes of Plotting

6. Trigonometric Curves

7. Multiple Plotting

8. Line Colors and Style

9. Change Type of Line

8. Support Vector Mechanics

1. Support Vector Machine

9. Decision Tree Complete Lecture

1. Decision Tree Complete Lecture

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تولید کننده: Udemy-Training