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Books > Computing & IT > Applications of computing > Artificial intelligence > Natural language & machine translation
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Natural Language Processing and Computational Linguistics - A practical guide to text analysis with Python, Gensim, spaCy, and Keras (Paperback)
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Natural Language Processing and Computational Linguistics - A practical guide to text analysis with Python, Gensim, spaCy, and Keras (Paperback)
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Work with Python and powerful open source tools such as Gensim and
spaCy to perform modern text analysis, natural language processing,
and computational linguistics algorithms. Key Features Discover the
open source Python text analysis ecosystem, using spaCy, Gensim,
scikit-learn, and Keras Hands-on text analysis with Python,
featuring natural language processing and computational linguistics
algorithms Learn deep learning techniques for text analysis Book
DescriptionModern text analysis is now very accessible using Python
and open source tools, so discover how you can now perform modern
text analysis in this era of textual data. This book shows you how
to use natural language processing, and computational linguistics
algorithms, to make inferences and gain insights about data you
have. These algorithms are based on statistical machine learning
and artificial intelligence techniques. The tools to work with
these algorithms are available to you right now - with Python, and
tools like Gensim and spaCy. You'll start by learning about data
cleaning, and then how to perform computational linguistics from
first concepts. You're then ready to explore the more sophisticated
areas of statistical NLP and deep learning using Python, with
realistic language and text samples. You'll learn to tag, parse,
and model text using the best tools. You'll gain hands-on knowledge
of the best frameworks to use, and you'll know when to choose a
tool like Gensim for topic models, and when to work with Keras for
deep learning. This book balances theory and practical hands-on
examples, so you can learn about and conduct your own natural
language processing projects and computational linguistics. You'll
discover the rich ecosystem of Python tools you have available to
conduct NLP - and enter the interesting world of modern text
analysis. What you will learn Why text analysis is important in our
modern age Understand NLP terminology and get to know the Python
tools and datasets Learn how to pre-process and clean textual data
Convert textual data into vector space representations Using spaCy
to process text Train your own NLP models for computational
linguistics Use statistical learning and Topic Modeling algorithms
for text, using Gensim and scikit-learn Employ deep learning
techniques for text analysis using Keras Who this book is forThis
book is for you if you want to dive in, hands-first, into the
interesting world of text analysis and NLP, and you're ready to
work with the rich Python ecosystem of tools and datasets waiting
for you!
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