To get the most out of this book
Readers should have basic knowledge of deep learning training pipelines, such as training convolutional neural networks for image classification. This book will mainly use high-level Keras APIs in TensorFlow 2, which is easy to learn. Should you need to refresh or learn TensorFlow 2, there are many free tutorials available online, such as the one on the official TensorFlow website, https://www.tensorflow.org/tutorials/keras/classification.
Training deep neural networks is computationally intensive. You can train the first few simple models using the CPU only. However, as we progress to more complex models and datasets in later chapters, the model training could take a few days before you start to see satisfactory results. To get the most out of this book, you should have access to the GPU to accelerate the model training time. There are also free cloud services, such as Google's Colab, that provide GPUs on which you can upload and run the code.
If you are using the digital version of this book, we advise you to type the code yourself or access the code via the GitHub repository (link available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.
