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Day06 Linear Regression 101

Pre-Read

  1. https://www.quora.com/What-is-supervised-learning
  2. A really simple explanation
  3. PennState Eberly College of Science
  4. Linear Regression
  5. Machine Learning Mastery 1
  6. Machine Learning Mastery 2

Learning Objectives

  1. Understand the intuition behind Linear Regression
  2. Understand the different notations used in Linear Regression
  3. Understand the Linear Regression Cost Function
  4. Understand the Linear Regression Closed Form Solution
  5. Understand the Gradient Descent Algorithm and the differences between Closed Form Solution and Gradient Descent
  6. Learn how to optimize Gradient Descent
  7. Learn about the assumptions in Linear Regression Algorithm
  8. Introduction to Linear Regression in sklearn

Hands-on Skills

Slides

@gslides

Notebooks

Code Demonstration

Assignments

Gradient Descent implementation

Post Reads

  1. Linear Regression in Python
  2. Linear Regression using Gradient Descent Tutorial
  3. CS229 - Andrew Ng, Stanford University

day06-linear-regression-101's People

Contributors

mudassirkhan19 avatar

Watchers

Soumendra Prasad Dhanee avatar James Cloos avatar Suraj Jadhav avatar PradeepJaiswar avatar Mayuresh Suresh Shilotri avatar  avatar Sangam Angre avatar Shweta Doshi avatar

Forkers

ameya-s

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