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LifestyleDeep Learning Foundation : Linear Regression and Statistics (Udemy.com)
Learn linear regression from scratch, Statistics, R-Squared, Python, Gradient descent, Deep Learning, Machine Learning
Created by: Jay Bhatt
Last updated July 2023
What you will learn
- Mathematics behind R-Squared, Linear Regression,VIF and more!
- Deep understating of Gradient descent and Optimization
- Program your own version of a linear regression model in Python
- Derive and solve a linear regression model, and implement it appropriately to data science problems
- Statistical background of Linear regression and Assumptions
- Assumptions of linear regression hypothesis testing
- Writing codes for T-Test, Z-Test and Chi-Squared Test in python
How it compares
Against the other 461 rated Udemy courses in Data Science on CourseDuck:
- Rating4.6 out of 5higher than 67% of them
- Reviews1,408#116 of 462 by number of reviews
- Length6.8 hoursshorter than 56% of them
- Last updatedJuly 2023earlier than 82% of them
Course Description
Hi Everyone welcome to new course which is created to sharpen your linear regression and statistical basics. linear regression is starting point for a data science this course focus is on making your foundation strong for deep learning and machine learning algorithms. In this course I have explained hypothesis testing, Unbiased estimators, Statistical test , Gradient descent. End of the course you will be able to code your own regression algorithm from scratch.
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Instructor Details
- 4.6 Rating
1,408 Reviews
Jay Bhatt
Hi my name is Jay Having 5 years of experience in a leading Data Science Company, I have completed my masters degree adv mathematics and FEM . I love making educational videos and content. check out my you-tube channel and all udamy tutorial and stay updated with new techniques of data science and machine learning. Hope you will enjoy this lovely journey of Data science and machine learning.
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Reviews
By Sandeep Chiluveru on 1/7/2024
Introduced and covered all the concepts of linear regression conveying its general purpose and the problems that it solves. This is a huge learning for newcomers into the field. Gives a nice foundation for higher learnings in future on the topic.
By Rajesh Prasad on 9/25/2023
Great course on Mathematics and explanation is presented with example
By Steve Ligon on 10/26/2022
This is very hard to listen to and understand key points, because of the accent being so strong. And the captions are totally missing making sense of what is being said.
By Anthony on 12/4/2020
This is a great course! It covers theory, math, intuition, and coding implementation of linear regression in Python.
By Tyler on 12/4/2020
This course is a great combination of hands on experience and in depth theoretical explanation of the mathematical concepts.
By Jonathan on 12/4/2020
Course was a great match. Jay has the right approach of doling out math and theory, (no matter how difficult) and then correlate it to coding.
By William on 12/4/2020
This course is exactly what I was looking for. The instructor does an impressive job making students understand they need to work hard in order to learned. The examples are clear, and the explanations of the theory is very interesting.
By Eric on 12/4/2020
A very good introduction to linear regression. The implementation of all the concepts from the ground up in code is an excellent way to drive home the concepts. My only complaint/wish would be to have a small section addressing the assumptions of linear regression, parts of which I feel were slightly glossed over.
By Simon Bale on 9/13/2020
Delivery is a bit slow. The concept are covered in detail with examples. Overall a good course for basics as well as beginner programming
By Garrison on 7/2/2020
I have taken other course of jay I should say I am a fan of his teaching style...
Quality Score
No CourseDuck member has rated this course yet. Taken it? Give each part a thumbs up or down.
Overall Score : 92 / 100
- Video Duration:
6.8h - Price: $49.99
- Provider: Udemy
- Updated:
July 2023 - Level:
All Levels - Language:
English - Certificate:
Yes
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