Deep Learning For Natural Language Processing - Machine Learning Mastery

Deep learning methods are achieving state-of-the-art results on challenging machine learning problems such as describing photos and translating text from one language to another. In this new laser-focused Ebook written in the friendly Machine Learning Mastery style that you're used to, finally cut through the math, research papers and patchwork descriptions about natural language processing. Using clear explanations, standard Python libraries and step-by-step tutorial lessons you will discover what natural language processing is, the promise of deep learning in the field, how to clean and prepare text data for modeling, and how to develop deep learning models for your own natural language processing projects. Click to jump straight to the packages. We are awash with text, from books, papers, blogs, tweets, news, and increasingly text from spoken utterances. Every day, I get questions asking how to develop machine learning models for text data. Working with text is hard as it requires drawing upon knowledge from diverse domains such as linguistics, machine learning, statistical natural language processing, and these days, deep learning. The problem with modeling text is that it is messy, and machine learning algorithms prefer well defined fixed-length inputs and outputs.