The reader should have some knowledge of Python, NumPy array manipulation, and linear algebra. In addition, you should be familiar with main concepts of[deep learning](https://en.wikipedia.org/wiki/Deep_learning).

To refresh the memory, you can take the[Python](https://docs.python.org/dev/tutorial/index.html) and[Linear algebra on n-dimensional arrays](https://numpy.org/doc/stable/user/tutorial-svd.html) tutorials.

To refresh the memory, you can take the[Python](https://docs.python.org/dev/tutorial/index.html) and[Linear algebra on n-dimensional arrays](https://numpy.org/numpy-tutorials/content/tutorial-svd.html) tutorials.

You are advised to read the[Deep learning](http://www.cs.toronto.edu/~hinton/absps/NatureDeepReview.pdf) paper published in 2015 by Yann LeCun, Yoshua Bengio, and Geoffrey Hinton, who are regarded as some of the pioneers of the field. You should also consider reading Andrew Trask's[Grokking Deep Learning](https://www.manning.com/books/grokking-deep-learning), which teaches deep learning with NumPy.