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It is in CSV format and includes the following information about cancer in the US: death rates, reported cases, US county name, income per county, population, demographics and more. The dataset contains data from, , and the American Community Survey. The OLS regression challenge tasks you with predicting cancer mortality rates for US counties. Using this data, you can experiment with predictive modeling, rolling linear regression and more.

The dataset comes in four CSV files: prices, prices-split-adjusted, securities and fundamentals. It contains 1338 rows of data and the following columns: age, gender, BMI, children, smoker, region and insurance charges.Ĭreated as a resource for technical analysis, this dataset contains historical data from the New York stock market. The data contains medical information and costs billed by health insurance companies. This dataset was inspired by the book Machine Learning with R by Brett Lantz.

The dataset includes the fish species, weight, length, height and width.

CDC data: nutrition, physical activity, obesityįrom the Behavioral Risk Factor Surveillance System at the CDC, this dataset includes information about physical activity, weight and average adult diet.īuilt for multiple linear regression and multivariate analysis, the Fish Market Dataset contains information about common fish species in market sales. 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.Ģ. This dataset includes data taken from about deaths due to cancer in the United States. Linear regression datasets for machine learning Additionally, some of the datasets on this list include sample regression tasks for you to complete with the data. 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. Every data scientist will likely have to perform linear regression tasks and predictive modeling processes at some point in their studies or career.