Category: Regression Algorithms
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Evaluating your Regression Model in Python
Code and data used can be found here: Repository In the previous episode we discussed multiple methods in which you can evaluate your regression model. At the end of the episode we also discussed a general method which you can apply. This article is split into two parts: Part 1 builds a multiple linear regression…
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Evaluating Regression Models
After building a machine learning model whether that is using simple linear regression or gradient boosting it is important to get an idea of just how well your model performs. This article is designed to give you an overview of some of the most common model evaluation methods for regression models along with their advantages…
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Polynomial Regression in Python
Code and data used can be found here: Repository Importing our Data The first step is to import our data into python. We can do that by going on the following link: Data Click on “code” and download ZIP. Locate WeatherDataP.csv and copy it into your local disc under a new file called ProjectData Note: WeatherData.csv…
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Understanding Polynomial Regression
This Article expands on Simple Linear Regression and Multiple Linear Regression, ensure you have a good understanding of these two topic areas before continuing. What is Polynomial Regression? Polynomial Regression is used to capture non-linear relationships between variables. For example: For linear relationships we use Linear Regression. Overview Take a look at the following graph…
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Multiple Linear Regression in Python
Code and data used can be found here: Repository This episode expands on Implementing Simple Linear Regression In Python. We extend our simple linear regression model to include more variables. Setting up your programming environment can be found in the first section of Ep 4.3. Importing our Data The first step is to import our data…
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Understanding Multiple Linear Regression
We have taken a look at Simple Linear Regression in Episode 4.1 where we had one variable x to predict y, but what if now we have multiple variables, not just x, but 𝑥₁,𝑥₂ and 𝑥₃ … to predict y — how would we approach this problem? I hope to explain in this article. Simple Linear Regression Recap…
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Simple Linear Regression in Python
Code and data used can be found here: Repository From the previous two episodes you should now know the underlying theory of Linear Regression, its purpose and how we use gradient descent in optimising our parameters. You can read them here: Episode 4.1, Episode 4.2 . Setting up your programming environment All programming in this series…
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Understanding Gradient Descent
This article plans to expand on episode 4.1, explaining Gradient Descent and how it is used to minimise our cost function in Linear Regression. Knowledge of derivatives and partial derivatives will be helpful. Linear Regression Recap From the previous episode we calculated the regression line for our humidity and temperature data to be: Which we…
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Understanding Simple Linear Regression
This article is designed to teach the underlying theory of linear regression. How to code and implement this algorithm in Python will be included in episode 4.3. This article also covers some basic Data Science Terminology which is important to know for future episodes. What is Linear Regression? Linear regression is a common supervised machine…
The Data Series 