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eBook on Natural Language Processing

eBook on Natural Language Processing

Natural Language Processing (NLP) is a field of computer science and artificial intelligence concerned with the interaction between computers and human (natural) languages. It involves the development of algorithms and computational models that enable machines to understand, interpret, generate, and respond to human language.

This book is suitable for both software developers as well as Business Leaders and Technical Project Managers / Technical Program Managers. 
The eBook has lessons and quiz and costs $49.99

To order, click here

Our eBook covers the following topics

1. Introduction to Natural Language Processing
What is Natural Language Processing (NLP)
Applications of NLP
NLP vs. Computational Linguistics
NLP vs. Speech Recognition
NLP vs. Text Mining
NLP vs. Machine Translation

2 Text Pre-processing
Tokenization
Stopword Removal
Stemming and Lemmatization
Lowercasing and Uppercasing
Punctuation and Special Character Removal
Removing HTML and XML Markup

3. Text Representation and Feature Engineering
One-hot Encoding
N-grams
Term Frequency-Inverse Document Frequency (TF-IDF)
Word Embeddings

4. Sentiment Analysis
What is Sentiment Analysis
Sentiment Analysis Techniques
Sentiment Analysis Use Cases
Sentiment Analysis Tools and Libraries

5. Named Entity Recognition
What is Named Entity Recognition
Named Entity Recognition Techniques
Named Entity Recognition Use Cases
Named Entity Recognition Tools and Libraries

6. Part-of-Speech Tagging
What is Part-of-Speech Tagging
Part-of-Speech Tagging Techniques
Part-of-Speech Tagging Use Cases
Part-of-Speech Tagging Tools and Libraries

7. Text Classification
What is Text Classification
Text Classification Techniques
Text Classification Use Cases
Text Classification Tools and Libraries

8. Topic Modeling
What is Topic Modeling
Topic Modeling Techniques
Topic Modeling Use Cases
Topic Modeling Tools and Libraries

9. Text Summarization
What is Text Summarization
Text Summarization Techniques
Text Summarization Use Cases
Text Summarization Tools and Libraries

10. Advanced NLP Techniques
Machine Translation
Text Generation
Chatbots and Dialogue Systems
Question Answering Systems

11. NLP in Production
Deploying NLP Models
Scaling NLP Solutions
NLP in the Cloud

12. Conclusion and Future of NLP
The Future of NLP
NLP and AI Integration
NLP Challenges and Opportunities

To order, click here

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