Inteligencia Artificial Aplicada a Procesamiento de Lenguaje Natural (NLP) con Python y Machine Learning.

Abstract

This book reflects the work done under research between teachers and researchers with the aim of being useful to the reader, the use of predictions when training a classified text algorithm in natural language processing (NLP) based on machine learning. Conformed of 4 chapters with the usefulness for the beginning to the world of the AI of the branch of natural language processing with Python in machine learning. Chapter 1 mentions concepts and the evolution of the different branches of knowledge that encompasses artificial intelligence (AI), the understanding of NLP, machine learning, types of learning to solve problems such as supervised, unsupervised and reinforcement. Chapter 2 deepens the NLP knowing the basic classification contents such as: LSTM techniques and design, tokeization, stopword, lemmatization, bag of Word (part of speech tagging). Chapter 3 is the structuring of this chapter to know the definitions of supervised learning models that are useful in NLP oriented to text classification. Chapter 4 is a case of prediction or degree of assertiveness of an algorithm modeling, the intention is to demonstrate the use of a model and several techniques applying NLP based on machine learning.