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.
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”.
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.
Watch on YouTube: Performing a linear regression in Google Sheets with TableTorch 7:16
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.
- How to create correlation matrix
- How to do linear regression
- How to do logistic regression
- How to convert categorical text data into a series of binary columns or a category identifier column
- How to perform a train-test or k-fold cross-validation sample split
- How to scale all columns at once with percentile rank or standard scaler
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