|Название: Deep Learning for Natural Language Processing: Develop Deep Learning Models for Natural Language in Python
Автор: Jason Brownlee
Издательство: Machine Learning Mastery Pty. Ltd.
Формат: pdf (true)
Размер: 10.1 MB
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.
Python is the go-to language for applied machine learning and deep learning, both in terms of demand from employers and employees. This is not least because it could be a renaissance for machine learning tools. I have focused on showing you how to use the best of breed Python tools for natural language processing such as Gensim and NLTK, and even a little scikit-learn. Key to getting results is speed of development, and for this reason, we use the Keras deep learning library as you can define, train, and use complex deep learning models with just a few lines of Python code.
Who Is This Book For?
This book is for developers that know some applied machine learning and some deep learning. Maybe you want or need to start using deep learning for text on your research project or on a project at work. This guide was written to help you do that quickly and efficiently by compressing years worth of knowledge and experience into a laser-focused course of hands-on tutorials.
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