To get the most out of this book

This book assumes an understanding of the Python language, specifically Python 3.6 and above. It is strongly recommended to have the Anaconda distribution of Python installed on your local systems. Any Anaconda distribution with support for Python 3.6 and above is good for running the examples in this book. 

In terms of hardware, this book assumes the availability of a microphone, speaker, and webcam on your computer. 

Software/Hardware covered in the book	OS Requirements
Anaconda distribution of Python and other Python packages	1 GB RAM minimum, 8 GB recommended 15 GB disk space
Code editor of your choice (Sublime Text 3 recommended)	2 GB RAM

 

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.

It is expected that you will try to implement the samples present in this book by yourself. In case you run into problems, you can reach out to us by emailing the authors – Sayak Paul ([email protected]) and Anubhav Singh ([email protected]). In case you are unable to run the samples provided in the code repo of the book, you can raise issues on the repo and we'll get back to you there!

Download the example code files

You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packtpub.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

1. Log in or register at www.packt.com.
2. Select the Support tab.
3. Click on Code Downloads.
4. Enter the name of the book in the Search box and follow the onscreen instructions.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

• WinRAR/7-Zip for Windows
• Zipeg/iZip/UnRarX for Mac
• 7-Zip/PeaZip for Linux

The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/Hands-On-Python-Deep-Learning-for-Web. In case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Download the color images

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: http://www.packtpub.com/sites/default/files/downloads/9781789956085_ColorImages.pdf.

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "We now need to import the saved model and weights from the model training step. Once we do so, we need to recompile the model and make its predict function using the make_predict_fuction() method."

A block of code is set as follows:

def remove_digits(s: str) -> str:
    remove_digits = str.maketrans('', '', digits)
    res = s.translate(remove_digits)
    return res

Any command-line input or output is written as follows:

python main.py

Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "Fill up the entries and click on Continue."

Warnings or important notes appear like this.

Tips and tricks appear like this.