DOC: Update another link to linear algebra tutorial

content/tutorial-nlp-from-scratch.md

@@ -31,7 +31,7 @@ Today, Deep Learning is getting adopted in everyday life and now it is more impo
 
 ## Prerequisites
 
-You are expected to be familiar with the Python programming language and array manipulation with NumPy. In addition, some understanding of Linear Algebra and Calculus is recommended. You should also be familiar with how Neural Networks work. For reference, you can visit the [Python](https://docs.python.org/dev/tutorial/index.html), [Linear algebra on n-dimensional arrays](https://numpy.org/doc/stable/user/tutorial-svd.html) and [Calculus](https://d2l.ai/chapter_appendix-mathematics-for-deep-learning/multivariable-calculus.html) tutorials.
+You are expected to be familiar with the Python programming language and array manipulation with NumPy. In addition, some understanding of Linear Algebra and Calculus is recommended. You should also be familiar with how Neural Networks work. For reference, you can visit the [Python](https://docs.python.org/dev/tutorial/index.html), [Linear algebra on n-dimensional arrays](https://numpy.org/numpy-tutorials/content/tutorial-svd.html) and [Calculus](https://d2l.ai/chapter_appendix-mathematics-for-deep-learning/multivariable-calculus.html) tutorials.
 
 To get a refresher on Deep Learning basics, You should consider reading [the d2l.ai book](https://d2l.ai/chapter_recurrent-neural-networks/index.html), which is an interactive deep learning book with multi-framework code, math, and discussions. You can also go through the [Deep learning on MNIST from scratch tutorial](https://numpy.org/numpy-tutorials/content/tutorial-deep-learning-on-mnist.html) to understand how a basic neural network is implemented from scratch.