Companies Home Search Profile

Natural Language Processing Fundamentals for Developers

Natural Language Processing Fundamentals for Developers

Download pdf

Natural Language Processing Fundamentals for Developers

Natural Language Processing Fundamentals for Developers

Category

Natural Language Processing

Data Mining

Author

Oswald Campesato

Publication

Mercury Learning and Information

0 View

This book is for developers who are looking for an overview of basic concepts in Natural Language Processing. It casts a wide net of techniques to help developers who have a range of technical backgrounds. Numerous code samples and listings are included to support myriad topics. The first chapter shows you various details of managing data that are relevant for NLP. The next pair of chapters contain NLP concepts, followed by another pair of chapters with Python code samples to illustrate those NLP concepts. Chapter 6 explores applications, e.g., sentiment analysis, recommender systems, COVID-19 analysis, spam detection, and a short discussion regarding chatbots. The final chapter presents the Transformer architecture, BERT-based models, and the GPT family of models, all of which were developed during the past three years and considered SOTA (state of the art). The appendices contain introductory material (including Python code samples) on regular expressions and probability/statistical concepts. Companion files with source code and figures are included (available for downloading with Amazon proof of purchase by writing to [email protected]).

Features
+Covers extensive topics related to natural language processing
+Includes separate appendices on regular expressions and probability/statistics
+Features companion files with source code and figures from the book (available for downloading with Amazon proof of purchase by writing to [email protected])

Brief TOC
1: Working with Data. 2: NLP Concepts (I). 3: NLP Concepts (II). 4. Algorithms and Toolkits (I). 5. Algorithms and Toolkits (II). 6: NLP Applications. 7: Transformer, BERT, and GPT. Appendices. A: Introduction to Regular Expressions. B: Introduction to Probability and Statistics.

About The Author
Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Clara and specializes in Deep Learning, NLP, Android, and TensorFlow. He is the author/co-author of over twenty-five books including TensorFlow 2 Pocket Primer, Python 3 for Machine Learning, and the Data Science Fundamentals Pocket Primer (all Mercury Learning).

'

Download pdf

ISBN-10

ISBN-13

9781683926573

Publisher

Mercury Learning and Information

Price

38.35

File Type

PDF

Page No.

Oswald Campesato

Oswald Campesato

Oswald is an education junkie: a former PhD Candidate in Mathematics (ABD) who has multiple MS and B ...

About the Author

Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Clara and specializes in Deep Learning, Java, NLP, Android, and TensorFlow. He is the author/co-author of over twenty-five books including TensorFlow 2 Pocket Primer, Python 3 for Machine Learning, and the Data Science Fundamentals Pocket Primer (all Mercury Learning and Information). --This text refers to the paperback edition.

Similar Books

Enjoying Natural Computing: Essays Dedicated to Mario de Jesús Pérez-Jiménez on the Occasion of His 70th Birthday (Lecture Notes in Computer Science, 11270)

Enjoying Natural Computing: Essays Dedicated to Mario de Jesús Pérez-Jiménez on the Occasion of His 70th Birthday (Lecture Notes in Computer Science, 11270)

Carmen Graciani

Natural Language Processing

Python Natural Language Processing Cookbook: Over 50 recipes to understand, analyze, and generate text for implementing language processing tasks

Python Natural Language Processing Cookbook: Over 50 recipes to understand, analyze, and generate text for implementing language processing tasks

Zhenya Antic

Natural Language Processing

Natural Language Processing with TensorFlow: The definitive NLP book to implement the most sought-after machine learning models and tasks, 2nd Edition

Natural Language Processing with TensorFlow: The definitive NLP book to implement the most sought-after machine learning models and tasks, 2nd Edition

Thushan Ganegedara

Machine Learning

Transformers for Natural Language Processing: Build, train, and fine-tune deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, and GPT-3, 2nd Edition

Transformers for Natural Language Processing: Build, train, and fine-tune deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, and GPT-3, 2nd Edition

Denis Rothman

Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python

Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python

Yuxi (Hayden) Liu

Machine Learning

The Kaggle Book: Data analysis and machine learning for competitive data science

The Kaggle Book: Data analysis and machine learning for competitive data science

Luca Massaron

Machine Learning

Deep Natural Language Processing and Ai Applications for Industry 5.0 (Advances in Computational Intelligence and Robotics)

Deep Natural Language Processing and Ai Applications for Industry 5.0 (Advances in Computational Intelligence and Robotics)

Poonam Tanwar

Artificial Intelligence

Natural Language Processing and Computational Linguistics: A practical guide to text analysis with Python, Gensim, spaCy, and Keras

Natural Language Processing and Computational Linguistics: A practical guide to text analysis with Python, Gensim, spaCy, and Keras

Bhargav Srinivasa-Desikan

Hands-On Transfer Learning with Python: Implement advanced deep learning and neural network models using TensorFlow and Keras

Hands-On Transfer Learning with Python: Implement advanced deep learning and neural network models using TensorFlow and Keras

Dipanjan Sarkar

Machine Learning for Text

Machine Learning for Text

Charu C. Aggarwal

Machine Learning

Pandas 1.x Cookbook: Practical recipes for scientific computing, time series analysis, and exploratory data analysis using Python, 2nd Edition

Pandas 1.x Cookbook: Practical recipes for scientific computing, time series analysis, and exploratory data analysis using Python, 2nd Edition

Ted Petrou

PostgreSQL 13 Cookbook: Over 120 recipes to build high-performance and fault-tolerant PostgreSQL database solutions

PostgreSQL 13 Cookbook: Over 120 recipes to build high-performance and fault-tolerant PostgreSQL database solutions

Avinash Vallarapu

The Kaggle Book: Data analysis and machine learning for competitive data science

The Kaggle Book: Data analysis and machine learning for competitive data science

Luca Massaron

Machine Learning

Hands-On Data Preprocessing in Python: Learn how to effectively prepare data for successful data analytics

Hands-On Data Preprocessing in Python: Learn how to effectively prepare data for successful data analytics

Roy Jafari

Cleaning Data for Effective Data Science: Doing the other 80% of the work with Python, R, and command-line tools

Cleaning Data for Effective Data Science: Doing the other 80% of the work with Python, R, and command-line tools

David Mertz

Hands-On Data Analysis with Pandas: A Python data science handbook for data collection, wrangling, analysis, and visualization, 2nd Edition

Hands-On Data Analysis with Pandas: A Python data science handbook for data collection, wrangling, analysis, and visualization, 2nd Edition

Stefanie Molin

Data Mining Approaches for Big Data and Sentiment Analysis in Social Media (Advances in Data Mining and Database Management)

Data Mining Approaches for Big Data and Sentiment Analysis in Social Media (Advances in Data Mining and Database Management)

Brij B Gupta

Hands-On Deep Learning with Apache Spark: Build and deploy distributed deep learning applications on Apache Spark

Hands-On Deep Learning with Apache Spark: Build and deploy distributed deep learning applications on Apache Spark

Guglielmo Iozzia

Other Authors' Books

Python 3 for Machine Learning

Python 3 for Machine Learning

Oswald Campesato

Python For Programmers

Python For Programmers

Oswald Campesato

Software Development

Data Science Fundamentals Pocket Primer

Data Science Fundamentals Pocket Primer

Oswald Campesato

SQL Pocket Primer

SQL Pocket Primer

Oswald Campesato

Dealing with Data: Pocket Primer

Dealing with Data: Pocket Primer

Oswald Campesato

Natural Language Processing

Other Publishing Books

Python Basics: A Self-Teaching Introduction

Python Basics: A Self-Teaching Introduction

H. Bhasin

Python 3 for Machine Learning

Python 3 for Machine Learning

Oswald Campesato

Python 2/E: An Introduction to Programming

Python 2/E: An Introduction to Programming

James R. Parker

Python For Programmers

Python For Programmers

Oswald Campesato

Software Development

Microsoft Access 2021 Programming Pocket Primer

Microsoft Access 2021 Programming Pocket Primer

Julitta Korol

Microsoft Access

Cluster Analysis and Data Mining: An Introduction

Cluster Analysis and Data Mining: An Introduction

Ronald S. King

Data Structures and Algorithms in C++: Pocket Primer (Pocket Primer Series)

Data Structures and Algorithms in C++: Pocket Primer (Pocket Primer Series)

Lee Wittenberg

3D Printing: An Introduction

3D Printing: An Introduction

Stephanie Torta

Wireless Sensor Networks: Architecture - Applications - Advancements

Wireless Sensor Networks: Architecture - Applications - Advancements

S. R. Vijayalakshmi

Wireless Networking

Data Science for IoT Engineers: A Systems Analytics Approach

Data Science for IoT Engineers: A Systems Analytics Approach

P. G. Madhavan

Internet Of Things

Big Data Using Hadoop and Hive

Big Data Using Hadoop and Hive

Nitin Kumar

User Reviews

Log in first to post a comment

Rating

0

0

0

0

0

average 0

Total votes0