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Natural Language Processing and Machine Learning for Developers

Autor Oswald Campesato
en Limba Engleză Paperback – 27 mai 2021
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.
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Specificații

ISBN-13: 9781683926184
ISBN-10: 1683926188
Pagini: 754
Dimensiuni: 178 x 229 x 42 mm
Greutate: 1.72 kg
Editura: Mercury Learning & Information

Notă biografică

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

Cuprins

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