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Data science: Learn linear regression from scratch and build your own working program in Python for data analysis.

## (1) Defining linear regression, deriving the solution

- Introduction and Outline
- What is machine learning? How does linear regression play a role?
- Introduction to Moore's Law Problem
- 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
- 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
- Generalization error, train and test sets
- Categorical inputs
- Brief overview of advanced linear regression and machine learning topics
- Exercises, practice, and how to get good at this
- BONUS: Where to get Udemy coupons and FREE deep learning material
- How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow

## (2) 1-D Linear Regression: Theory and Code

- Introduction and Outline
- What is machine learning? How does linear regression play a role?
- Introduction to Moore's Law Problem
- 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
- 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
- Generalization error, train and test sets
- Categorical inputs
- Brief overview of advanced linear regression and machine learning topics
- Exercises, practice, and how to get good at this
- BONUS: Where to get Udemy coupons and FREE deep learning material
- How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow

## (3) Multiple linear regression and polynomial regression

- Introduction and Outline
- What is machine learning? How does linear regression play a role?
- Introduction to Moore's Law Problem
- 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
- 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
- Generalization error, train and test sets
- Categorical inputs
- Brief overview of advanced linear regression and machine learning topics
- Exercises, practice, and how to get good at this
- BONUS: Where to get Udemy coupons and FREE deep learning material
- How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow

## (4) Practical machine learning issues

- Introduction and Outline
- What is machine learning? How does linear regression play a role?
- Introduction to Moore's Law Problem
- 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
- 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
- Generalization error, train and test sets
- Categorical inputs
- Brief overview of advanced linear regression and machine learning topics
- Exercises, practice, and how to get good at this
- BONUS: Where to get Udemy coupons and FREE deep learning material
- How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow

## (5) Appendix

- Introduction and Outline
- What is machine learning? How does linear regression play a role?
- Introduction to Moore's Law Problem
- 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
- 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
- Generalization error, train and test sets
- Categorical inputs
- Brief overview of advanced linear regression and machine learning topics
- Exercises, practice, and how to get good at this
- BONUS: Where to get Udemy coupons and FREE deep learning material
- How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow

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