Bayesian Methods for Hackers: Probabilistic Programming and by Cameron Davidson-Pilon

By Cameron Davidson-Pilon

Grasp Bayesian Inference via sensible Examples and Computation–Without complicated Mathematical Analysis

Bayesian tools of inference are deeply common and intensely strong. in spite of the fact that, such a lot discussions of Bayesian inference depend upon intensely complicated mathematical analyses and synthetic examples, making it inaccessible to someone and not using a robust mathematical heritage. Now, even though, Cameron Davidson-Pilon introduces Bayesian inference from a computational standpoint, bridging concept to practice–freeing you to get effects utilizing computing power.

Bayesian tools for Hackers illuminates Bayesian inference via probabilistic programming with the strong PyMC language and the heavily comparable Python instruments NumPy, SciPy, and Matplotlib. utilizing this procedure, you could achieve potent strategies in small increments, with out huge mathematical intervention.

Davidson-Pilon starts off by way of introducing the ideas underlying Bayesian inference, evaluating it with different concepts and guiding you thru construction and coaching your first Bayesian version. subsequent, he introduces PyMC via a sequence of unique examples and intuitive motives which were sophisticated after large consumer suggestions. You’ll methods to use the Markov Chain Monte Carlo set of rules, decide upon applicable pattern sizes and priors, paintings with loss capabilities, and observe Bayesian inference in domain names starting from finance to advertising and marketing. as soon as you’ve mastered those thoughts, you’ll continuously flip to this advisor for the operating PyMC code you want to jumpstart destiny projects.

Coverage includes

• studying the Bayesian “state of mind” and its sensible implications
• knowing how desktops practice Bayesian inference
• utilizing the PyMC Python library to software Bayesian analyses
• construction and debugging types with PyMC
• trying out your model’s “goodness of fit”
• establishing the “black box” of the Markov Chain Monte Carlo set of rules to work out how and why it works
• Leveraging the facility of the “Law of enormous Numbers”
• studying key innovations, corresponding to clustering, convergence, autocorrelation, and thinning
• utilizing loss features to degree an estimate’s weaknesses in accordance with your pursuits and wanted outcomes
• picking applicable priors and knowing how their impact alterations with dataset size
• Overcoming the “exploration as opposed to exploitation” difficulty: determining whilst “pretty good” is sweet enough
• utilizing Bayesian inference to enhance A/B testing
• fixing info technology difficulties while merely small quantities of knowledge are available

Cameron Davidson-Pilon has labored in lots of parts of utilized arithmetic, from the evolutionary dynamics of genes and ailments to stochastic modeling of monetary costs. His contributions to the open resource neighborhood comprise lifelines, an implementation of survival research in Python. knowledgeable on the college of Waterloo and on the self sufficient college of Moscow, he at present works with the web trade chief Shopify.

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Extra info for Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference

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The outcomes of these tests will show you what security holes can — or cannot — be fixed to make your wireless network more secure. Not to worry, we won’t leave you hanging with a bunch of vulnerabilities to fix. We’ll outline various countermeasures you can use to fix the weaknesses you find. In the next few sections, we outline the various types of security attacks to establish the basis for the vulnerability tests you’ll be running against your wireless network. Non-technical attacks These types of attacks exploit various human weaknesses, such as lack of awareness, carelessness, and being too trusting of strangers.

On the other hand, sometimes they attack simply to get under the administrator’s skin. Sometimes they are seeking revenge. Hackers may want to use a system so they can attack other people’s networks under disguise. Or maybe they’re bored, and just want to see what information is flying through the airwaves, there for the taking. The “high-end” uberhackers go where the money is — literally. These are the guys who break into online banks, e-commerce sites, and internal corporate databases for financial gain.

By planning things out (in the ways we covered in Chapter 2) and having specific goals and methods — even checklists — you’ll know where you’re headed and you’ll know when your testing is complete. It’ll make your job a lot easier, and document the steps you take. Speaking of which . . 32 Part I: Building the Foundation for Testing Wireless Networks Keep a log of what you do and when. com). Such visual samples come in handy when you know you won’t be able to reproduce the same information on your screen again.

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