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# Deep Learning Prerequisites: Linear Regression in Python

7.99 \$
Video Introducing this tutorial

Introduction and Outline :
Introduction and Outline
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What is machine learning? How does linear regression play a role?
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Introduction to Moore's Law Problem
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What can linear regression be used for?
1 question
How to Succeed in this Course

1-D Linear Regression: Theory and Code :
Define the model in 1-D, derive the solution (Updated Version)
Define the model in 1-D, derive the solution
Coding the 1-D solution in Python
Determine how good the model is - r-squared
R-squared in code
Demonstrating Moore's Law in Code
R-squared
1 question

Multiple linear regression and polynomial regression :
Define the multi-dimensional problem and derive the solution (Updated Version)
Define the multi-dimensional problem and derive the solution
How to solve multiple linear regression using only matrices
Coding the multi-dimensional solution in Python
Polynomial regression - extending linear regression (with Python code)
Predicting Systolic Blood Pressure from Age and Weight
R-squared
1 question

Practical machine learning issues :
01:05:27
What do all these letters mean?
Interpreting the Weights
Generalization error, train and test sets
Generalization and Overfitting Demonstration in Code
Categorical inputs
One-hot encoding
1 question
Probabilistic Interpretation of Squared Error
L2 Regularization - Theory
L2 Regularization - Code
The Dummy Variable Trap
Bypass the Dummy Variable Trap with Gradient Descent
L1 Regularization - Theory
L1 Regularization - Code
L1 vs L2 Regularization

Conclusion and Next Steps :
Brief overview of advanced linear regression and machine learning topics
Exercises, practice, and how to get good at this

Appendix :
BONUS: Where to get Udemy coupons and FREE deep learning material
Preview
How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow
How to Code by Yourself (part 1)
How to Code by Yourself (part 2)