Kedia / Rasu Hands-On Python Natural Language Processing

Explore tools and techniques to analyze and process text with a view to building real-world NLP applications
1. Auflage 2020
ISBN: 978-1-83898-258-4
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 316 Seiten

No detailed description available for "Hands-On Python Natural Language Processing".

Autoren/Hrsg.

Kedia, Aman

Rasu, Mayank

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Spracherkennung, Sprachverarbeitung
• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse

Inhaltsverzeichnis

Table of Contents - Understanding the Basics of NLP
- NLP Using Python
- Building your NLP Vocabulary
- Transforming Text into Data Structures
- Word Embeddings and Distance Measurements for Text
- Exploring Sentence-, Document-, and Character-Level Embeddings
- Identifying Patterns in Text using Machine Learning
- From Human Neurons to Artificial Neurons for Understanding Text
- Applying Convolutions to Text
- Capturing Temportal Relationships in Text
- State of the Art in NLP

Über Autor(innen)

Kedia Aman:
Aman Kedia is a data enthusiast and lifelong learner. He is an avid believer in Artificial Intelligence (AI) and the algorithms supporting it. He has worked on state-of-the-art problems in Natural Language Processing (NLP), encompassing resume matching and digital assistants, among others. He has worked at Oracle and SAP, trying to solve problems leveraging advancements in AI. He has four published research papers in the domain of AI.Rasu Mayank:
Mayank Rasu is the author of the book Hands-On Natural Language Processing with Python. He has more than 12 years of global experience as a data scientist and quantitative analyst in the investment banking domain. He has worked at the intersection of finance and technology and has developed and deployed AI-based applications in the finance domain, which include sentiment analyzer, robotics process automation, and deep learning-based document reviewers. Mayank is also an educator and has trained/mentored working professionals on applied AI.