How to Get Queries Resolved
1 min
Download Resources
1 min
Regression Equation and Terminologies
10 min
Regression Equation and Terminologies
5 min
Formula for Coefficients
4 min
Coefficients Computation from Scratch
5 min
Linear Regression and Regularisation
- Linear Regression is one of the most widely and foundational regression algorithm
of machine learning. Learn how to build a regression from scratch and how
to overcome the problem of overfitting in machine learning. Not just that,learn
about various advancedregression algorithms and metrics to evaluate the models.
Created by Selva Prabhakaran
-
50 Video Lessons
-
English
-
English captions
Validity Period: 365 days
Already Subscribed? Click here to access your courses
- Course Certificate
- Code Walkthroughs
- Practice Data
- Money Back if not satisfied
- Algorithms explanation
- 2h 26m of Self-paced videos
- Downloadable resources
- Q&A sessions with experts
What you will learn
01
What is Linear Regression
What is Linear Regression
and where can it be used?
02
Build Regression Model from scratch
03
Perform thr Pre-model
Perform thr Pre-model
build Analysis
04
Check if the model is overfitted
Check if the model is overfitted
and learn to check the assumptions
of linear regression and rectify
05
Find the influential
Find the influential
points in the data
06
Learn the advanced
Learn the advanced
regression algorithms
07
Evaluate the model using
Evaluate the model using
various evaluation metrics
08
Implement Linear Regression
Implement Linear Regression
in a project and solve it
end to end
Course Curriculum
8 Modules | 56 Sessions | 7 hour 31 min Total Time
Introduction to Linear Regression
Sessions: 7 | Time: 31 min
Regression Algorithm from scratch: Gradient Descent
Sessions: 5 | Time: 43 min
Model Building and Concepts Part- 1
Sessions: 9 | Time: 59 min
Model Building and Concepts Part- 2
Sessions: 10 | Time: 57 min
Model Selection Approaches
Sessions: 8 | Time: 1 hr 23 min
Regularization Modelling Approaches
Sessions: 7 | Time:1 hr 14 min
Outlier Resistant and Advanced Regression
Sessions: 8 | Time:1 hr 22 min
Maximum Estimation for Linear Regression
Sessions: 2 | Time: 22 min
Requirements
- Basic Maths and Logical Reasoning
- Curiosity about Data Science
- Learning Mindset
Who should attend this course?
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Future Data Scientists and ML Engineers
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Product Managers, Program Managers, Scrum Masters working in ML/Data science project
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Software/Data engineers interested in quantitative analysis
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Software engineers interfacing with data science team
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Executives who have to lead or interact with Data Scientists
Instructor
Selva Prabhakaran Principal Data Scientist
My name is Selva, and I am super excited to mentor you on this project!
I head the Data Science team for a global Fortune 500 company and over the last
10 years of my data science experience I’ve deployed 20+ global products. I’m
also the Founder & Chief Author of Machine Learning Plus, which has over 4M
annual readers.
I specialize in covering the in-depth intuition and maths of any concept or
algorithm. And based on my existing student requests, I’ve put up the series of
courses and projects with detailed explanations – just like an on the job
experience. Hope you love it!
-
4.5+Instructor rating
-
200+ reviews
-
10K+students
-
15+ Courses
Validity Period: 365 days
Already Subscribed? Click here to access your courses
- Workshop Certificate
- Code Walkthroughs
- Practice Data
- Money Back if not satisfied
- Algorithms explanation
- 2h 26m of Self-paced videos
- Downloadable resources
- Q&A sessions with experts