To get the most out of this book
The reader is expected to have a good understanding of Python programming and a working environment with Python 3.7+. A good theoretical understanding of mathematics for deep learning will be beneficial. MXNet 1.9.1 and the supplementary GluonCV and GluonNLP libraries will need to be installed as well (versions 0.10). These MXNet/Gluon requirements are described in detail in Chapter 1 and can be followed along by the reader. All code examples have been tested with Ubuntu 20.04, Python 3.10.12, MXNet 1.9.1, GluonCV 0.10 and GluonNLP 0.10. However, they should work with future releases too.
|
Software/hardware covered in the book |
Operating system requirements |
|
Python3.7+ |
Linux (Ubuntu recommended) |
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MXNet 1.9.1 |
|
|
GluonCV 0.10 |
|
|
GluonNLP 0.10 |
In order to reproduce similar results to those described in Chapter 8, the reader will need access to a machine with multiple GPUs installed.
If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book’s GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.
