[New!] Simple Vs. Multiple Vs. Polynomial Regression | By Dr. Ry @Stemplicity
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- Опубліковано 20 лип 2024
- This tutorial explains the difference between Simple Linear Regression, multiple Linear Regression and Polynomial Regression in a fun, practical and easy way!
In this tutorial, you will learn the following:
• Simple Linear Regression theory and intuition
• Multiple Linear Regression theory and intuition
• Polynomial Regression theory and intuition
• What is the difference between Simple, Multiple and Polynomial regression?
• When to use Simple, Multiple and Polynomial regression?
Machine Learning is a sub-field of Artificial Intelligence that enables machines to improve at a given task with experience.
Machine Learning is an extremely hot topic; the demand for experienced machine learning engineers and data scientists has been steadily growing in the past 5 years.
Here’s a link to my new machine learning regression course on Udemy:
www.udemy.com/machine-learnin...
Subscribe to my channel to get the latest updates, we will be releasing new videos on weekly basis:
/ @professor-ryanahmed
The purpose of this course is to provide students with knowledge of key aspects of machine learning regression techniques in a practical, easy and fun way. Regression is an important machine learning technique that works by predicting a continuous (dependent) variable based on multiple other independent variables. Regression strategies are widely used for stock market predictions, real estate trend analysis, and targeted marketing campaigns.
The course provides students with practical hands-on experience in training machine learning regression models using real-world data set. This course covers several technique in a practical manner, including:
• Simple Linear Regression
• Multiple Linear Regression
• Polynomial Regression
• Logistic Regression
• Decision trees regression
• Ridge Regression
• Lasso Regression
• Artificial Neural Networks for Regression analysis
• Regression Key performance indicators
The course is targeted towards students wanting to gain a fundamental understanding of machine learning regression models. Basic knowledge of programming is recommended. However, these topics will be extensively covered during early course lectures; therefore, the course has no prerequisites, and is open to any student with basic programming knowledge. Students who enroll in this course will master machine learning regression models and can directly apply these skills to solve real world challenging problems.
I thought this was the best video I’ve seen. You were precise and scholarly.
Definetly the clearest explanation
Thank you for being sharp, short and still insightful in your explanation. Really helped a lot 😊
wow! indeed: sharp, short, insightful, clear
Thank you!!! I spent about a day looking for a simple explanation; I've been struggling differentiating the differences, thank you for your simple examples and including the equation instead solving a complex one!
You are doing the world a great service with such clarity. Thank you so much!!!
Thank you for fast and easy explanation
Simple short and to the point....great 👏👏👏
Thank you! Excellent break down.
Such a good explanation, thanks!
Very clear and concise .... great help, thanks
You're Awesome, Thank you!
fantastic!
This video was so easy to learn. Thanks!
Thank you, it was simple and understandable
Well explained😍
just amazing
Bayesian linear regression explain please
great
can I build a multiple polynomial regression?
Hi, Dr. Ryan, I could not send you a message through Udemy, so forgive me I have to write you in some way.
I just finished your ML courses, 172 sessions, but have hard time to find the code to get exam bonus, tries two codes F2@9, and F2@9&B, none of them worked. I saw many people have the same problem in Q&A.
you are so popular now, hope this msg find you well.
Great video, I have been following you in ML world.
Is it possible to have multiple polynomial regression ? like : y = b0 + x1^2 + x1^3 +x2^2+x2^3 ?
seems likely :-)
i have a homework with multiple polynomial regression and i get struggled with it if you know something please helpppp meee!!! :(
Very well explained
why can't google recommend such videos?
But Increasing order in polynomial regression leads to overfiting