zane 0 Comments

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

Visit Deep Learning Prerequisites: Linear Regression in Python (Udemy) to read more...

Categories:

,
Share this post