Book Image

Python Machine Learning Blueprints - Second Edition

By : Alexander Combs, Michael Roman
Book Image

Python Machine Learning Blueprints - Second Edition

By: Alexander Combs, Michael Roman

Overview of this book

Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to put your knowledge and skills into practice and use the Python ecosystem to cover key domains in machine learning. This second edition covers a range of libraries from the Python ecosystem, including TensorFlow and Keras, to help you implement real-world machine learning projects. The book begins by giving you an overview of machine learning with Python. With the help of complex datasets and optimized techniques, you’ll go on to understand how to apply advanced concepts and popular machine learning algorithms to real-world projects. Next, you’ll cover projects from domains such as predictive analytics to analyze the stock market and recommendation systems for GitHub repositories. In addition to this, you’ll also work on projects from the NLP domain to create a custom news feed using frameworks such as scikit-learn, TensorFlow, and Keras. Following this, you’ll learn how to build an advanced chatbot, and scale things up using PySpark. In the concluding chapters, you can look forward to exciting insights into deep learning and you'll even create an application using computer vision and neural networks. By the end of this book, you’ll be able to analyze data seamlessly and make a powerful impact through your projects.
Table of Contents (13 chapters)

What does research tell us about virality?

Understanding sharing behavior is big business. As consumers become increasingly blind to traditional advertising year on year, the push is on to go beyond simple pitches to tell engaging stories. And increasingly, the success of these endeavors is measured in social shares. Why go to so much trouble? Because, as a brand, every share I receive represents another consumer I've reached—all without spending an additional cent.

Because of this value, several researchers have examined sharing behavior in the hope of understanding what motivates it. Among the reasons researchers have found are the following:

  • To provide practical value to others (an altruistic motive)
  • To associate ourselves with certain ideas and concepts (an identity motive)
  • To bond with others around a common emotion (a communal motive)

With regard to the last...