To get the most out of this book

You are expected to have a basic foundation of knowledge of Python, the basic machine learning algorithms, and some basic Python libraries, such as TensorFlow and Keras, in order to create smart cognitive actions for your projects.

Download the example code files

The code bundle for the book is hosted on GitHub at https://github.com/PacktPublishing/Python-Machine-Learning-By-Example-Third-Edition. 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: https://static.packt-cdn.com/downloads/9781800209718_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. For example; "Then, we'll load the en_core_web_sm model and parse the sentence using this model."

A block of code is set as follows:

>>> from sklearn import datasets
>>> iris = datasets.load_iris()
>>> X = iris.data[:, 2:4]
>>> y = iris.target

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

conda install pytorch torchvision -c pytorch

Bold: Indicates a new term, an important word, or words that you see on the screen, for example, in menus or dialog boxes, also appear in the text like this. For example: "A new window will pop up and ask us which collections (the Collections tab in the following screenshot) or corpus (the identifiers in the Corpora tab in the following screenshot) to download and where to keep the data."

Warnings or important notes appear like this.

Tips and tricks appear like this.