Soup up text processing with latest techniques in natural language processing in python. Key Features * Learn how to extract word embeddings representation. * Learn how to use the Random Forest and the Decision Trees algorithms. * Learn how to apply curriculum and reinforcement learning. Book Description Machine Learning and Python offer unique opportunities to exploit data that involve text and more specifically human language. There is a rapid demand for professionals that can process text data and extract meaningful information out of it. There is a plethora of textbooks that either present complicated theoretical concepts or focus disproportionately on Python code. This book steers an intermediate way and keeps the right balance between theory and practice based on various case studies. A good metaphor on which this work builds upon is the relation between an experienced craftsperson and his/her trainee. Based on the current problem, the former picks a tool from the toolbox, explains its utility, and puts it into action. Each chapter follows the same pattern for presenting the material. At a high level, it consists of three steps that include: (1) acquire some intuition on the data (exploratory data analysis), (2) put in action a few machine learning algorithms (for training and inference), and (3) evaluate their performance on the problem under study (metrics). By the end of this book, you will be able to apply a gamut of techniques with Python for text preprocessing, text representation, dimensionality reduction, machine learning, visualization, and performance evaluation. What you will learn * Perform exploratory data analysis on text corpora. * Use text preprocessing techniques. * Know how text data can be represented. * Apply dimensionality reduction for visualization and classification. * Understand fundamental concepts of text ML. * Incorporate algorithms and models for text ML. * Evaluate the results of the text analysis. * Know the tools for obtaining and storing text data. Who This Book Is For The target audience of this book are data science professionals, NLP Engineers, Machine Learning developers. Professionals like Data Scientists with good knowledge in programming that seek more information on the field, or want to do a gentle career shift in machine learning for text will find this book essential. Beginner level knowledge of python programming is needed to learn from this book.

Book Information
ISBN 9781803242385
Author Nikos Tsourakis
Format Paperback
Page Count 471
Imprint Packt Publishing Limited
Publisher Packt Publishing Limited
Weight(grams) 75g