Deep Learning Prerequisites: Linear Regression in Python (Update)
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Created by: Lazy Programmer Inc.
Data science: Learn linear regression from scratch and build your own working program in Python for data analysis. What you'll learn

Derive and solve a linear regression model, and apply it appropriately to data science problems
Program your own version of a linear regression model in Python

Requirements

How to take a derivative using calculus
Basic Python programming
For the advanced section of the course, you will need to know probability

Description

This course teaches you about one popular technique used in machine learning, data science and statistics: linear regression. We cover the theory from the ground up: derivation of the solution, and applications to real-world problems. We show you how one might code their own linear regression module in Python.

Linear regression is the simplest machine learning model you can learn, yet there is so much depth that you'll be returning to it for years to come. That's why it's a great introductory course if you're interested in taking your first steps in the fields of:

deep learning

machine learning

data science

statistics

In the first section, I will show you how to use 1-D linear regression to prove that Moore's Law is true.

What's that you say? Moore's Law is not linear?

You are correct! I will show you how linear regression can still be applied.

In the next section, we will extend 1-D linear regression to any-dimensional linear regression - in other words, how to create a machine learning model that can learn from multiple inputs.