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  • 1
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (300 pages)
    Edition: 2nd edition
    Parallel Title: Erscheint auch als Downey, Allen B. Think Bayes
    RVK:
    Keywords: Electronic books ; local
    Abstract: If you know how to program, you're ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical formulas, using discrete probability distributions rather than continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer and you'll begin to apply these techniques to real-world problems. Bayesian statistical methods are becoming more common and more important, but not many resources are available to help beginners. Based on undergraduate classes taught by author Allen Downey, this book's computational approach helps you get a solid start. Use your programming skills to learn and understand Bayesian statistics Work with problems involving estimation, prediction, decision analysis, evidence, and Bayesian hypothesis testing Get started with simple examples, using coins, dice, and a bowl of cookies Learn computational methods for solving real-world problems
    Note: Online resource; Title from title page (viewed May 25, 2021) , Mode of access: World Wide Web.
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (170 pages)
    Edition: 1st edition
    Parallel Title: Erscheint auch als Calavera, David Linux observability with BPF
    RVK:
    Keywords: Electronic books ; local ; LINUX ; Programmierung ; Leistungsbewertung
    Abstract: Want to master the BPF virtual machine in the Linux Kernel? This practical guide shows you how to write applications that use BPF to observe and modify the kernel’s behavior on demand—without having prior knowledge of Linux Kernel development. David Calavera and Lorenzo Fontana introduce concepts to help systems engineers understand the BPF program lifecycle. If you have knowledge about performance optimization, networking, and security, this book shows you how to inject code to monitor, trace, and observe events in the kernel in a secure way—without the need to recompile the kernel or reboot the system. You’ll find code examples in C, Go, and Python.
    Note: Online resource; Title from title page (viewed September 25, 2019)
    Library Location Call Number Volume/Issue/Year Availability
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