Top 10 Regression Datasets for Machine Learning Projects

On Hacker Noon, I will be sharing some of my best-performing machine learning articles. This listicle on datasets built for regression or linear regression tasks has been upvoted many times on Reddit and reshared dozens of times on various social media platforms. I hope Hacker Noon data scientists find it useful as well!

Every data scientist will likely have to perform linear regression tasks and predictive modeling processes at some point in their studies or career. For those of you looking to learn more about the topic or complete some sample assignments, this article will introduce open linear regression datasets you can download today. Additionally, some of the datasets on this list include sample regression tasks for you to complete with the data.

Linear Regression Datasets for Machine Learning

1. Cancer Linear Regression

This dataset includes data taken from cancer.gov about deaths due to cancer in the United States. Along with the dataset, the author includes a full walkthrough on how they sourced and prepared the data, their exploratory analysis, model selection, diagnostics, and interpretation.

2. CDC Data: Nutrition, Physical Activity, Obesity

From the Behavioral Risk Factor Surveillance System at the CDC, this dataset includes information about physical activity, weight, and average adult diet.

3. Fish Market Dataset

Built for multiple linear regression and multivariate analysis, the Fish Market Dataset contains information about common fish species in market sales. The dataset includes the fish species, weight, length, height, and width.

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Top 10 Regression Datasets for Machine Learning Projects
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Top Machine Learning Projects in Python For Beginners [2021]

If you want to become a machine learning professional, you’d have to gain experience using its technologies. The best way to do so is by completing projects. That’s why in this article, we’re sharing multiple machine learning projects in Python so you can quickly start testing your skills and gain valuable experience.

However, before you begin, make sure that you’re familiar with machine learning and its algorithm. If you haven’t worked on a project before, don’t worry because we have also shared a detailed tutorial on one project:

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Top Machine Learning Projects in Python For Beginners [2021] | upGrad blog

If you want to become a machine learning professional, you’d have to gain experience using its technologies. The best way to do so is by completing projects. That’s why in this article, we’re sharing multiple machine learning projects in Python so you can quickly start testing your skills and gain valuable experience.

However, before you begin, make sure that you’re familiar with machine learning and its algorithm. If you haven’t worked on a project before, don’t worry because we have also shared a detailed tutorial on one project:

The Iris Dataset: For the Beginners

The Iris dataset is easily one of the most popular machine learning projects in Python. It is relatively small, but its simplicity and compact size make it perfect for beginners. If you haven’t worked on any machine learning projects in Python, you should start with it. The Iris dataset is a collection of flower sepal and petal sizes of the flower Iris. It has three classes, with 50 instances in every one of them.

We’ve provided sample code on various places, but you should only use it to understand how it works. Implementing the code without understanding it would fail the premise of doing the project. So be sure to understand the code well before implementing it.

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