Data Science Fundamentals Pocket Primer: Pocket Primer
Autor Oswald Campesatoen Limba Engleză Paperback – 8 iun 2021
- Includes a concise introduction to Python 3 and linear algebra
- Provides a thorough introduction to data visualization and regular expressions
- Covers NumPy, Pandas, R, and SQL
- Introduces probability and statistical concepts
- Features numerous code samples throughout
- Companion files with source code and figures
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Specificații
ISBN-13: 9781683927334
ISBN-10: 1683927338
Pagini: 450
Dimensiuni: 152 x 229 x 25 mm
Greutate: 0.65 kg
Ediția:1. Auflage
Editura: Mercury Learning and Information
Colecția Pocket Primer
Seria Pocket Primer
ISBN-10: 1683927338
Pagini: 450
Dimensiuni: 152 x 229 x 25 mm
Greutate: 0.65 kg
Ediția:1. Auflage
Editura: Mercury Learning and Information
Colecția Pocket Primer
Seria Pocket Primer
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: Working with Data
2: Introduction to Probability and Statistics
3: Linear Algebra Concepts
4: Introduction to Python
5: Introduction to NumPy
6: Introduction to Pandas
7: Introduction to R
8: Regular Expressions
9: SQL and NoSQL
10: Data Visualization
Index
2: Introduction to Probability and Statistics
3: Linear Algebra Concepts
4: Introduction to Python
5: Introduction to NumPy
6: Introduction to Pandas
7: Introduction to R
8: Regular Expressions
9: SQL and NoSQL
10: Data Visualization
Index