TableTorch add-on for Google Sheets

Fit linear or logistic regression model right inside Google Sheets spreadsheet in a few clicks with single add-on, the TableTorch.

Video tutorials

Correlation matrix computation

Watch on YouTube: Compute a correlation matrix in Google Sheets with TableTorch 4:33

Correlation matrix is a rather useful tool for the analysis of interdependency between the columns (features) of a dataset. In this video, you will learn how to compute a correlation matrix in Google Sheets either by entering CORREL() function many times, sometimes even hundreds of times, or just by clicking a single button in the Gaujasoft TableTorch add-on for Google Sheets.

Linear regression

Watch on YouTube: Performing a linear regression in Google Sheets with TableTorch 7:16

Linear regression fits a model predicting single dependent variable (label) via multiplication of one or many independent variables (features) by their respective coefficients.

This video describes linear regression in a nutshell and shows how you can do it right inside Google Sheets with the TableTorch add-on. It uses vehicle prices dataset sample to fit a model estimating a car’s price based on its features such as the engine’s power, gearbox kind, model, year, and so on.

Random forest regression

Watch on YouTube: Random forest regression in Google Sheets with TableTorch add-on 5:56

Random forest regression fits a model that uses an ensemble of decision trees to estimate a continuous variable.

In this video it’s shown how to apply the random forest regression algorithm to fit a model of a used car price in Google Sheets with the TableTorch add-on. It uses the same vehicle prices dataset sample as is shown in the video about linear regression.

Binary classifier and logistic regression: full tutorial

Watch on YouTube: Binary classifier | Logistic regression | Real-world business data analysis 18:17

This video uses a real-world dataset with records of attempts to sell bank clients a financial product via a direct phone call. It demonstrates numeric features extraction techniques and the usage of the TableTorch add-on for Google Sheets to fit a logistic regression model, insert an estimation column and build a binary classifier.

The shown techniques are useful for practically any task involving a binary value estimation, that is, choosing 1 or 0, for instance, 1 for “likely to subscribe” and 0 for “unlikely to subscribe”.


TableTorch uses your sheet data solely for the purposes of an initiated request, i.e. it does not store nor transfer your data to any third-party. Review our Privacy policy for more details.

See also

Google, Google Sheets, Google Workspace and YouTube are trademarks of Google LLC. Gaujasoft TableTorch is not endorsed by or affiliated with Google in any way.