To get the most out of this book

1. Utilize all the links provided to gain a better understanding of some of the terms used in this book.
2. The Internet is the biggest university in today's world. Use websites such as YouTube, Udemy, edX, Lynda, and Coursera for their videos about various deep learning and machine learning concepts.
3. Don't just read the book and forget about it. Practically implement each step while reading the book. It is recommended that you have your Jupyter Notebook open while going through each recipe so that you can work through every recipe while reading the book and simultaneously check the outputs you obtain for each of the steps mentioned.

Download the example code files

You can download the example code files for this book from your account at www.packtpub.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.packtpub.com.
2. Select the SUPPORT tab.
3. Click on Code Downloads & Errata.
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/Apache-Spark-Deep-Learning-Cookbook. 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!

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: "Save under the trained folder inside the working directory."

A block of code is set as follows:

print('Total Rows')
df.count()
print('Rows without Null values')
df.dropna().count()
print('Row with Null Values')
df.count()-df.dropna().count()

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

nltk.download("punkt")
nltk.download("stopwords")

Bold: Indicates a new term, an important word, or words that you see on screen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "Right-click on the page and click on Save As..."

Warnings or important notes appear like this.

Tips and tricks appear like this.