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Python Data Analytics
Python Data Analytics
Python Data Analytics

Python Data Analytics

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Python Data AnalyticsWith Pandas, NumPy, and Matplotlib\nAuthor(s): Fabio Nelli\nFormat: Paperback\nPublisher: APress, United States\nImprint: APress\nISBN-13: 9781484295311, 978-1484295311\nSynopsis\nExplore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn.\nThis third edition is fully updated for the latest version of Python and its related libraries, and includes coverage of social media data analysis, image analysis with OpenCV, and deep learning libraries. Each chapter includes multiple examples demonstrating how to work with each library. At its heart lies the coverage of pandas, for high-performance, easy-to-use data structures and tools for data manipulation\nAuthor Fabio Nelli expertly demonstrates using Python for data processing, management, and information retrieval. Later chapters apply what you've learns

Python Data Analytics

Python Data AnalyticsWith Pandas, NumPy, and Matplotlib\nAuthor(s): Fabio Nelli\nFormat: Paperback\nPublisher: APress, United States\nImprint: APress\nISBN-13: 9781484295311, 978-1484295311\nSynopsis\nExplore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn.\nThis third edition is fully updated for the latest version of Python and its related libraries, and includes coverage of social media data analysis, image analysis with OpenCV, and deep learning libraries. Each chapter includes multiple examples demonstrating how to work with each library. At its heart lies the coverage of pandas, for high-performance, easy-to-use data structures and tools for data manipulation\nAuthor Fabio Nelli expertly demonstrates using Python for data processing, management, and information retrieval. Later chapters apply what you've learns

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