ГПНТБ России - Полное описание

Государственная публичная
научно-техническая библиотека России

Основана в 1958 году

Полное описание

Marin, Ivan. Big data analysis with Python : combine Spark and Python to unlock the powers of parallel computing and machine learning / Ivan Marin, Ankit Shukla and Sarang VK. - Birmingham, UK : Packt Publishing, 2019. - 5 p. - URL: https://cat.gpntb.ru/?id=FT/ShowFT&sid=37f0e474910301c08e6a0d9657a1afa3. - ISBN 1789950732. - ISBN 9781789950731. - Текст : электронный.
Содержание:
Chapter 1: The Python Data Science Stack -- Chapter 2: Statistical Visualizations -- Chapter 3: Working with Big Data Frameworks -- Chapter 4: Diving Deeper with Spark -- Chapter 5: Handling Missing Values and Correlation Analysis -- Chapter 6: Exploratory Data Analysis -- Chapter 7: Reproducibility in Big Data Analysis -- Chapter 8: Creating a Full Analysis Report
Рубрики:
Big data
Python (Computer program language)
Cloud computing
Machine learning
Big data
Cloud computing
Machine learning
Python (Computer program language)

Аннотация: Processing big data in real time is challenging due to scalability, information inconsistency, and fault tolerance. Big Data Analysis with Python teaches you how to use tools that can control the data avalanche for you. With this book, you'll learn effective techniques to aggregate data into useful dimensions for posterior analysis, extract ...

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Marin Ivan. Big data analysis with Python : combine Spark and Python to unlock the powers of parallel computing and machine learning / Ivan Marin, Ankit Shukla and Sarang VK., 2019. - 5 с. (Введено оглавление). - Текст : электронный.

Marin Ivan. Big data analysis with Python : combine Spark and Python to unlock the powers of parallel computing and machine learning / Ivan Marin, Ankit Shukla and Sarang VK., 2019. - 5 с. (Введено оглавление). - Текст : электронный.

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Marin Ivan. Big data analysis with Python : combine Spark and Python to unlock the powers of parallel computing and machine learning / Ivan Marin, Ankit Shukla and Sarang VK., 2019. - 5 с. (Введено оглавление). - Текст : электронный.

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