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Supervised Machine Learning: Complete Masterclass [2023]
Machine Learning, artificial intelligence, supervised machine learning, simple linear regression, and KNN model
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- < 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 Distribution
Allah 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
Machine Learning, Artificial Intelligence, and Supervised Machine Learning
Supervised Machine Learning Explained
Regression Analysis for SML
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15
Classification of SML -
16
What is Regression
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17
Example of Classification
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18
Types of Classification
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19
Binary Classification
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20
Multi-Class Classification
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21
Multi-Labeled Classification
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22
Regression Example
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23
Simple Linear Regression
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24
Multi-Linear Regression
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25
Polynomial Regression
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26
Graph of SLR
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27
Graph of Polynomial Regression
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28
Regression Code in Python
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29
Data Preprocessing
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30
Model Development
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31
SSR/SST
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32
Use of SciKit in Programming
KNN-Model for SML
Decision Tree
Data Visualization for SML
Support Vector Mechanics
Decision Tree Complete Lecture
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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Course details
Video
7 hours
Certificate of Completion
Full lifetime access
Access on mobile and TV
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