Natural Language Processing and Machine Learning for Developers
Autor Oswald Campesatoen Limba Engleză Paperback – 11 iun 2021
- 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.
Preț: 361.55 lei
Preț vechi: 451.94 lei
-20%
Puncte Express: 542
Carte disponibilă
Livrare economică 22 iunie-06 iulie
Livrare prin curier în România Termenul estimat este afișat lângă disponibilitate.
Transport gratuit de la 400.00 lei Plată online sau ramburs, în funcție de opțiunile comenzii.
Retur gratuit în 14 zile Comandă securizată și suport în română.
Specificații
ISBN-13: 9781683926184
ISBN-10: 1683926188
Pagini: 788
Dimensiuni: 178 x 229 x 42 mm
Greutate: 1.31 kg
Ediția:1. Auflage
Editura: Mercury Learning and Information
ISBN-10: 1683926188
Pagini: 788
Dimensiuni: 178 x 229 x 42 mm
Greutate: 1.31 kg
Ediția:1. Auflage
Editura: Mercury Learning and 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
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