Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Natural Language Processing and Computational Linguistics: A practical guide to text analysis with Python, Gensim, spaCy, and Keras

Buy

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 Description

Modern 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 For

This 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!

Table of Contents

  1. What is Text Analysis?
  2. Python Tips for Text Analysis
  3. spaCy's Language Models
  4. Gensim – Vectorizing text and transformations and n-grams
  5. POS-Tagging and its Applications
  6. NER-Tagging and its Applications
  7. Dependency Parsing
  8. Top Models
  9. Advanced Topic Modelling
  10. Clustering and Classifying Text
  11. Similarity Queries and Summarization
  12. Word2Vec, Doc2Vec and Gensim
  13. Deep Learning for text
  14. Keras and spaCy for Deep Learning
  15. Sentiment Analysis and ChatBots
(HTML tags aren't allowed.)

Machine Learning Using R: With Time Series and Industry-Based Use Cases in R
Machine Learning Using R: With Time Series and Industry-Based Use Cases in R

Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition shows you how to work with a machine-learning algorithm and use it to build a ML model from raw data. You will see how to use R programming with TensorFlow, thus avoiding the effort of learning Python...

Beginning Data Science with Python and Jupyter: Use powerful tools to unlock actionable insights from data
Beginning Data Science with Python and Jupyter: Use powerful tools to unlock actionable insights from data

Getting started with data science doesn't have to be an uphill battle. This step-by-step guide is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction.

Key Features

  • Get up and running with the Jupyter ecosystem and some example datasets
  • ...
Deep Learning for Computer Vision: Expert techniques to train advanced neural networks using TensorFlow and Keras
Deep Learning for Computer Vision: Expert techniques to train advanced neural networks using TensorFlow and Keras

Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasks

Key Features

  • Train different kinds of deep learning model from scratch to solve specific problems in Computer Vision
  • Combine the power of Python, Keras, and TensorFlow to...

Learn Keras for Deep Neural Networks: A Fast-Track Approach to Modern Deep Learning with Python
Learn Keras for Deep Neural Networks: A Fast-Track Approach to Modern Deep Learning with Python

Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras.

The overall...

Building Chatbots with Python: Using Natural Language Processing and Machine Learning
Building Chatbots with Python: Using Natural Language Processing and Machine Learning
Build your own chatbot using Python and open source tools. This book begins with an introduction to chatbots where you will gain vital information on their architecture. You will then dive straight into natural language processing with the natural language toolkit (NLTK) for building a custom language processing platform for...
Developing Bots with Microsoft Bots Framework: Create Intelligent Bots using MS Bot Framework and Azure Cognitive Services
Developing Bots with Microsoft Bots Framework: Create Intelligent Bots using MS Bot Framework and Azure Cognitive Services
Develop Intelligent Bots using Microsoft Bot framework (C# and Node.js), Visual Studio Enterprise & Code, Microsoft Azure and Cognitive Services. This book shows you how to develop great Bots, publish to Azure and register with Bot portal so that customers can connect and communicate using famous...
©2019 LearnIT (support@pdfchm.net) - Privacy Policy