Designing Data-Intensive Applications : The Big Ideas Behind Reliable USA STOCK

“Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems” by Martin Kleppmann is a comprehensive textbook published by O’Reilly Media in 2017. The book covers topics in data modeling and design, focusing on how to build reliable and scalable desktop applications with databases. With 614 pages, this trade paperback is a valuable resource for anyone looking to learn about designing data-intensive applications in a practical and informative manner.

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Python for Data Analysis Data Wrangling with Pandas NumPy and Jupyter FS

“Python for Data Analysis: Data Wrangling with Pandas, NumPy, and Jupyter” by Wes McKinney is a comprehensive textbook published by O’Reilly Media. This book covers essential topics in data analysis, including data visualization, processing, and mining, all using the popular programming language Python. With a strong focus on practical applications, this text is designed for students and professionals looking to deepen their understanding of data analysis techniques. The book’s 579 pages provide detailed insights and guidance on working with data using various tools and techniques in the Python ecosystem.

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