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Natural Language Processing and Machine Learning for Developers
Paperback
May 2021
9781683926184
More details
- Publisher
Mercury Learning and Information - Published
28th May 2021 - ISBN 9781683926184
- Language English
- Pages 754 pp.
- Size 7" x 9"
$64.95
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May 2021
9781683926160
More details
- Publisher
Mercury Learning and Information - Published
20th May 2021 - ISBN 9781683926160
- Language English
- Pages 754 pp.
- Size 7" x 9"
$64.95
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May 2021
9781683926177
More details
- Publisher
Mercury Learning and Information - Published
20th May 2021 - ISBN 9781683926177
- Language English
- Pages 754 pp.
- Size 7" x 9"
$169.95
This book is for developers who are looking for an introduction to basic concepts in NLP and machine learning. Numerous code samples and listings are included to support myriad topics. The first two chapters contain introductory material for NumPy and Pandas, followed by chapters on NLP concepts, algorithms and toolkits, machine learning, and NLP applications. The final chapters include examples of NLP tasks using TF2 and Keras, the Transformer architecture, BERT-based models, and the GPT family of models. The appendices contain introductory material (including Python code samples) for various topics, including data and statistics, Python3, regular expressions, Keras, TF2, Matplotlib and Seaborn. Companion files with source code and figures are included.
FEATURES:
- Covers extensive topics related to natural language processing and machine learning
- Includes separate appendices on data and statistics, regular expressions, data visualization, Python, Keras, TF2, and more
- Features companion files with source code and color figures from the book.
The companion files are available online by emailing the publisher with proof of purchase at info@merclearning.com.
1: Introduction to NumPy
2: Introduction to Pandas
3: NLP Concepts (I)
4: NLP Concepts (II)
5. Algorithms and Toolkits (I)
6. Algorithms
and Toolkits (II)
7: Introduction to Machine Learning
8: Classifiers in
Machine Learning
9: NLP Applications
10: NLP and TF2 / Keras
11: Transformer, BERT, and GPT
Appendices
A: Data and Statistics
B: Introduction
to Python
C: Introduction to Regular Expressions
D: Introduction to Keras
E: Introduction to TF2
F: Data Visualization
Index
Oswald Campesato
Oswald Campesato specializes in Deep Learning, Python, Data Science, and generative AI. He is the author/co-author of over forty-five books including Google Gemini for Python, Large Language Models, and GPT-4 for Developers (all Mercury Learning).
Computer Science; Data Analytics; Natural Language Processing; Machine Learning