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Chollet Discusses the Types of Tensors Typically Encountered in Deep \bullet

question 55

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Chollet discusses the types of tensors typically encountered in deep learning: \bullet A 0D (0-dimensional) tensor is one value and is known as a xe "scalar value"scalar.
\bullet A 1D tensor is similar to a one-dimensional array and is known as a xe "vector"vector. A 1D tensor might represent a sequence, such as hourly temperature readings from a sensor or the words of one movie review.
\bullet A 2D tensor is similar to a two-dimensional array and is known as a xe "matrix"matrix. A 2D tensor could represent a grayscale image in which the tensor's two dimensions are the image's width and height in pixels, and the value in each element is the intensity of that pixel.
Which of the following statements a) , b) or c) about additional types of tensors is false?


Definitions:

Contribution Margin Ratio

A financial metric that shows the percentage of sales revenue that exceeds variable costs, indicating how much revenue contributes to fixed costs and profit.

Break-Even Point

The point where total costs and total revenues are equal, leading to no profit or loss from production or sales.

Fixed Costs

Costs such as rent, salaries, and insurance are invariant, unaffected by the quantity of production or sales.

Cost Volume Profit Analysis

A financial analysis method used to determine how changes in costs and volume affect a company's operating income and net income.

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