Book Image

Machine Learning Techniques for Text

By : Nikos Tsourakis
Book Image

Machine Learning Techniques for Text

By: Nikos Tsourakis

Overview of this book

With the ever-increasing demand for machine learning and programming professionals, it's prime time to invest in the field. This book will help you in this endeavor, focusing specifically on text data and human language by steering a middle path among the various textbooks that present complicated theoretical concepts or focus disproportionately on Python code. A good metaphor this work builds upon is the relationship between an experienced craftsperson and their trainee. Based on the current problem, the former picks a tool from the toolbox, explains its utility, and puts it into action. This approach will help you to identify at least one practical use for each method or technique presented. The content unfolds in ten chapters, each discussing one specific case study. For this reason, the book is solution-oriented. It's accompanied by Python code in the form of Jupyter notebooks to help you obtain hands-on experience. A recurring pattern in the chapters of this book is helping you get some intuition on the data and then implement and contrast various solutions. By the end of this book, you'll be able to understand and apply various techniques with Python for text preprocessing, text representation, dimensionality reduction, machine learning, language modeling, visualization, and evaluation.
Table of Contents (13 chapters)

Introducing social networks

In the late 1960s, the famous psychologist Stanley Milgram decided to investigate the small-world concept, which states that the entire world is connected through short chains of acquaintances. Performing an ingenious experiment, Milgram asked a few hundred people from various locations to get a letter to a stranger in Boston. The participants were given information about the target recipient and instructed to send the letter to someone they knew that would more likely know that individual. The following person in the chain had to repeat the same task and send the letter to someone even closer. When Milgram examined the letters that reached the target, he realized they had changed hands about six times on average. The result demonstrated that, on average, any two individuals in the US are separated by five connections, known by the phrase six degrees of separation.

Although this outcome can be debated for many reasons, it paved the way for similar experiments...