Tensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment.
The tf.linalg.gramSchmidt() function is used to orthogonalize the vectors using the Gram-Schimdt process.
Syntax:
tf.linalg.gramSchmidt( xs )
Parameters:
- xs ( a tf.Tensor1D array or tf.Tensor2D): These are the vectors that are to be orthogonalized.
Return Value: It returns a tf.Tensor1D array or tf.Tensor2D.
Example 1:
Javascript
const tf = require("@tensorflow/tfjs")   // Creating a 2-D tensor const input = tf.tensor2d([     [3, 7],     [4, 6] ]);   // Getting the orthogonalized vector let result = tf.linalg.gramSchmidt(input);   result.print(); |
Output:
Tensor
[[0.3939193, 0.919145 ],
[0.919145 , -0.3939194]]
Example 2:
Javascript
const tf = require("@tensorflow/tfjs")   // Creating a 2-D tensor const input = tf.tensor2d([     [5, 7, 2],     [7, 6, 9],     [1, 2, 3] ]);   // Getting the orthogonalized vector let result = tf.linalg.gramSchmidt(input);   result.print(); |
Output:
Tensor
[[0.5661386, 0.792594 , 0.2264554],
[0.1283516, -0.3561312, 0.925579 ],
[-0.814256, 0.4949402 , 0.3033505]]
Reference: https://js.tensorflow.org/api/latest/#linalg.gramSchmidt
Whether you’re preparing for your first job interview or aiming to upskill in this ever-evolving tech landscape, neveropen Courses are your key to success. We provide top-quality content at affordable prices, all geared towards accelerating your growth in a time-bound manner. Join the millions we’ve already empowered, and we’re here to do the same for you. Don’t miss out – check it out now!
