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  • Book Overview & Buying The Python Workshop Second Edition
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The Python Workshop Second Edition

The Python Workshop Second Edition - Second Edition

By : Wade, Mario Corchero Jiménez , Bird, Dr. Lau Cher Han, Graham Lee
4.6 (19)
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The Python Workshop Second Edition

The Python Workshop Second Edition

4.6 (19)
By: Wade, Mario Corchero Jiménez , Bird, Dr. Lau Cher Han, Graham Lee

Overview of this book

Python is among the most popular programming languages in the world. It’s ideal for beginners because it’s easy to read and write, and for developers, because it’s widely available with a strong support community, extensive documentation, and phenomenal libraries – both built-in and user-contributed. This project-based course has been designed by a team of expert authors to get you up and running with Python. You’ll work though engaging projects that’ll enable you to leverage your newfound Python skills efficiently in technical jobs, personal projects, and job interviews. The book will help you gain an edge in data science, web development, and software development, preparing you to tackle real-world challenges in Python and pursue advanced topics on your own. Throughout the chapters, each component has been explicitly designed to engage and stimulate different parts of the brain so that you can retain and apply what you learn in the practical context with maximum impact. By completing the course from start to finish, you’ll walk away feeling capable of tackling any real-world Python development problem.
Table of Contents (16 chapters)
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13
Chapter 13: The Evolution of Python – Discovering New Python Features

Convolutional neural networks

Although deep learning performs well on tabular regression and classification datasets, deep learning has a bigger advantage when making predictions from unstructured data such as images or text.

When it comes to classifying images, deep learning shines by analyzing data not one-dimensionally, but two-dimensionally, using convolutional neural networks, or CNNs for short.

Convolutional neural networks are among the strongest machine learning algorithms in the world today for classifying images. In this section, you will learn the basic theory behind convolutions before building your own CNN.

MNIST

MNIST is the name of a famous dataset of handwritten digits from 1998 that has been widely used in computer vision. The dataset consists of 60K training images and 10K test images.

Google Colab includes a smaller sample of 20K training images, along with the 10K test images, that may be directly accessed in a Colab notebook and prepared for machine...

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The Python Workshop Second Edition
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