Applications of Tensor Broadcasting
Tensor Broadcasting is widely used in the Machine learning, deep learning and Data analysis applications etc. where there involve the operations between the tensors of different shapes, sizes and dimensions.
- Image Processing: Images are multi-dimensional arrays of pixels. When we apply different filters, transformations, resolutions, color contrasts to a image different pixel values of different tensors to adjusts them in different resolutions, dimensions while performing different operations on the image. Technique of Tensor Broadcasting helps in performing these operations easily by aligning different dimensions and shapes of tensors of images. resizing, changing color from RGB to greyscale. Tensor Broadcasting extends or compress images to smaller or larger resolutions and also preserving the content of the image.
- Signal preprocessing: Like images signals are also multi-dimensional, speech recognition & classification are the signal of 1-dimensional, Radar signals used for detecting and tracking signal in these are multi-dimensional. When we apply filters, transformations & feature extraction operations on signals of different lengths, Broadcasting of tensor helps to do these tasks easily by systematically aligning these signals in different dimensions.
- Data Analysis operations: When we analyze and manipulate the data by applying different operations such as data cleaning, transformations and feature engineering on datasets of different shapes and sizes, tensor broadcasting helps in performing these operations more smoothly because we know tensors will be involving in this operation which might be of different in sizes, shapes and dimensions. Tensor broadcasting handles these tensors in these complex operations of large datasets.
These are just few applications of tensor broadcasting but there are even more wide range of applications of these techniques as it helps in many different to handles the operations related to multi-dimensional arrays.
Tensor Broadcasting
Tensor broadcasting is a concept of array processing libraries like TensorFlow and NumPy, it allows for implicit element-wise operations between arrays of different shapes. In this article, we will learn about tensor broadcasting, it’s significance and steps to perform tensor broadcasting.
Table of Content
- Tensor Broadcasting
- Significance of Tensor Broadcasting in Array Operations
- Prerequisites
- Step by step process to perform Tensor Broadcasting
- Applications of Tensor Broadcasting
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