Deep Learning Foundation : Linear Regression and Statistics
What you'll 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
Requirements
- Jupyter notebook and simple python programming
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.
Who this course is for:
- Python developers curious about data science
- data science and machine leaning engineers
Instructor
![Jay Bhatt](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 3.7 Instructor Rating
- 3,454 Reviews
- 28,552 Students
- 3 Courses
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.