Machine Learning, artificial intelligence, supervised machine learning, simple linear regression, and KNN model
What you will learn
Machine Learning
Artificial Intelligence
Supervised Machine Learning
Supervised ML Model
What is Regression?
Simple LR
Multi-LR
Polynomial Regression
Model Development
Data Preprocession
Regression Coding
Scikit Programming
Collection of Data
Splitting of Data
Poly-Scatter Plot
KNN-Model for SML
Decision Tree
Data Visualization for SML
Support Vector Mechanics
Description
- < Step-by-step explanation of more than 7 hours of video lessons on Supervised Machine Learning: Complete Masterclass [2023]>
- <Instant reply to your questions asked during lessons>
- <Weekly live talks on Supervised Machine Learning: Complete Masterclass [2023]. You can raise your questions in a live session as well>
- <Helping materials like notes, examples, and exercises>
- <Solution of quizzes and assignments>
This course has been designed for Supervised Machine Learning. The course has explained from basics of Supervised Machine Learning and it finishes on a pro level. The real-life examples of Supervised Machine Learning have been added as well to make the course valuable for the learners.
What you will learn:
- Machine Learning
- Artificial Intelligence
- Supervised Machine Learning
- Supervised ML Model
- What is Regression?
- Simple LR
- Multi-LR
- Polynomial Regression
- Model Development
- Data Preprocessing
- Regression Coding
- Scikit Programming
- Collection of Data
- Splitting of Data
- Poly-Scatter Plot
- KNN-Model for SML
- Decision Tree
- Data Visualization for SML
- Support Vector mechanics.
- scatter Plots
- Matplotlib Glitches
- Colors in Scattering
- Plot Vs Scatter Plot
- Bar Plotting
- Multiple Bar Plot
- Stacked and Sub Plots
- Histogram Plot
- Data Set
- Data DistributionAllah Ditta is your lead instructor – a Ph.D. and lecturer making a living from teaching Supervised Machine Learning, and data science.
You’ll get premium support and feedback to help you become more confident with data science!
We can’t wait to see you on the course!
Enroll now, and we’ll help you improve your data science skills!
AD Chauhdry
Tayyab Rashid
English
language
Content
Introduction
Introduction
Machine Learning, Artificial Intelligence, and Supervised Machine Learning
Machine Learning Introduction
Table of Content
How AI Work?
Types of AI
Application of AI
Domains of AI
What is Machine Learning?
How ML Works?
Classification of ML
Trends in ML
Supervised ML
Supervised ML Algorithms 1
SML Algorithms 2
Supervised Machine Learning Explained
Classification of SML
What is Regression
Example of Classification
Types of Classification
Binary Classification
Multi-Class Classification
Multi-Labeled Classification
Regression Example
Simple Linear Regression
Multi-Linear Regression
Polynomial Regression
Graph of SLR
Graph of Polynomial Regression
Regression Code in Python
Data Preprocessing
Model Development
SSR/SST
Use of SciKit in Programming
Regression Analysis for SML
Example Simple Linear Regression
Collection of Data
Plotting SLR
Preprocessing of Data
Splitting Data
SLR Score
PR in Python
Poly-Scatter Plot
KNN-Model for SML
K-Nearest Neighbor
KNN Classification
Label Encoder
KNN Model Development
SK Learn
Importing Data Set
Selection of Model
Decision Tree
What is a Decision Tree?
How to Code Decision Tree?
Decision Tree Regression
Data Visualization for SML
What is Data Visualization?
Import Matplotlib
Plot in Matplotlib
Simple Plotting
Axes of Plotting
Trigonometric Curves
Multiple Plotting
Line Colors and Style
Change Type of Line
Support Vector Mechanics
Support Vector Machine
Decision Tree Complete Lecture
Decision Tree Complete Lecture