Gaujasoft

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”.

Privacy

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.