SQL Pocket Primer

Oswald Campesato

ISBN 10: 1683928148 / ISBN 13: 9781683928140

Editore: Mercury Learning And Information, De Gruyter Mär 2022, 2022

Riguardo questo articolo

This item is printed on demand - it takes 3-4 days longer - Neuware -No detailed description available for 'SQL Pocket Primer'. 310 pp. Englisch.

Codice articolo 9781683928140

Dati bibliografici

• Titolo: SQL Pocket Primer
• Editore: Mercury Learning And Information, De Gruyter Mär 2022
• Data di pubblicazione: 2022
• Lingua: Inglese
• ISBN 10: 1683928148
• ISBN 13: 9781683928140
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 229 L x 152 A x 17 P (millimetri) 229 millimetri di larghezza per 152 millimetri di altezza per 17 millimetri di profondità
• Peso: 452 grammi

Descrizione articolo

Riassunto

As part of the best-selling Pocket Primer series, this book is primarily for data scientists and machine learning engineers who want to expand their current knowledge of SQL using MySQL as the primary RDBMS. It includes Python-based code samples to access data from a MySQL table in a Pandas data frame and Java-based code samples for accessing data in a MySQL database, along with XML documents and JSON documents. The book also introduces NoSQL, presents an overview of MongoDB, and SQLite--an open-source RDBMS availableon mobile devices. The final chapter of the book covers a diverse set of miscellaneous topics, such as normalization, schemas, database optimization, and performance. Numerous code samples and listings are included to support myriad topics. Companion files with source code and figures are available from the publisher.

FEATURES:

• Covers extensive topics related to SQL, using MySQL as the primary RDBMS

• Introduces NoSQL, presents an overview of MongoDB, and SQLite--an open-source RDBMS available on mobile devices

• Features companion files with source code and figures from the book

Informazioni sull?autore

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).