Monte Carlo software | Computational statistics | Free Bayesian statistics software | Probabilistic software

Stan (software)

Stan is a probabilistic programming language for statistical inference written in C++. The Stan language is used to specify a (Bayesian) statistical model with an imperative program calculating the log probability density function. Stan is licensed under the New BSD License. Stan is named in honour of Stanislaw Ulam, pioneer of the Monte Carlo method. Stan was created by a development team consisting of 34 members that includes Andrew Gelman, Bob Carpenter, Matt Hoffman, and Daniel Lee. (Wikipedia).

Stan (software)
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Open Source vs. Closed Source Software

In this video, you’ll learn more about the differences between open-source software and closed-source software. Visit https://edu.gcfglobal.org/en/basic-computer-skills/ for more technology, software, and computer tips. We hope you enjoy!

From playlist Technology Trends

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the Internet (part 1)

An intro to the core protocols of the Internet, including IPv4, TCP, UDP, and HTTP. Part of a larger series teaching programming. See codeschool.org

From playlist The Internet

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How To Test Software Performance

What are the best types of software performance testing? What does the performance of a system really mean and how should we measure it? Performance testing is something of a black art. Performance testing tools aren’t enough alone to define a performance testing strategy. In this episod

From playlist Automated Testing

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the Internet (part 2)

An intro to the core protocols of the Internet, including IPv4, TCP, UDP, and HTTP. Part of a larger series teaching programming. See codeschool.org

From playlist The Internet

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Don't Build Perfect Software

Many of us strive for perfection in software development, is this really an appropriate target to aim for? Perfect code is an illusion. Software engineering is an empirical discipline, and the software we create is only ever correct in a narrow context, from a technical and a social perspe

From playlist Software Engineering

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The Monte Carlo Algorithm - George Dyson

The story of how early computing heros John von Neumann, Stan Ulam, Nicholas Metropolis, and others created the foundations of computer science (and the hydrogen bomb).

From playlist Ignite Foo Camp 2013

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Stanford Seminar - 4004 Microprocessors

Stanley Mazor, Tom Pittman, Edwin Lee (MIT), Hap Warner (Intel), and Brian A. Berg (Berg Software Design) January 19, 2022 View the full playlist: https://www.youtube.com/playlist?list=PLoROMvodv4rMWw6rRoeSpkiseTHzWj6vu

From playlist Stanford EE380-Colloquium on Computer Systems - Seminar Series

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SDS 507: Bayesian Statistics — with Rob Trangucci

Rob Trangucci joins us to discuss his work and study in Bayesian statistics and how he applies it to real-world problems. In this episode you will learn: • Getting Rob on the show [5:43] • Stan [7:08] • Gradients [15:50] • What is Bayesian statistics? [20:44] • Multi-modal deep learning [

From playlist Super Data Science Podcast

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The Future of Robotics and Artificial Intelligence (Andrew Ng, Stanford University, STAN 2011)

(May 21, 2011) Andrew Ng (Stanford University) is building robots to improve the lives of millions. From autonomous helicopters to robotic perception, Ng's research in machine learning and artificial intelligence could result one day in a robot that can clean your house. STAN: Society, T

From playlist Event | STAN: Society, Technology, Art and Nature

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The Computer Chronicles - Second Hand Computers (1986)

Special thanks to archive.org for hosting these episodes. Downloads of all these episodes and more can be found at: http://archive.org/details/computerchronicles

From playlist The Computer Chronicles 1986 Episodes

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The Computer Chronicles - Computer Bowl VI Part 2 (1994)

Special thanks to archive.org for hosting these episodes. Downloads of all these episodes and more can be found at: http://archive.org/details/computerchronicles

From playlist The Computer Chronicles - Computer Bowl Competitions

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Statistical Rethinking 2022 Lecture 08 - Markov chain Monte Carlo

Slides and other course materials: https://github.com/rmcelreath/stat_rethinking_2022 Music: Intro: https://www.youtube.com/watch?v=E06X1NXRdR4 Skate1 vid: https://www.youtube.com/watch?v=GCr0EO41t8g Skate1 music: https://www.youtube.com/watch?v=o3WvAhOAoCg Skate2 vid: https://www.youtube

From playlist Statistical Rethinking 2022

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Unix for Programmers - My Computer Science Degree in the Real World

I took a unix for programmers in college while pursuing my computer science degree. Today as a software engineer, I want to see what was carried over from that classroom to the real world of software development. ---------------------------------------------------------- I share and docu

From playlist Computer Science

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The Computer Chronicles - Business Applications (1985)

Special thanks to archive.org for hosting these episodes. Downloads of all these episodes and more can be found at: http://archive.org/details/computerchronicles

From playlist The Computer Chronicles 1985 Episodes

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Introduction to IP: Crash Course Intellectual Property #1

This week, Stan Muller launches the Crash Course Intellectual Property mini-series. So, what is intellectual property, and why are we teaching it? Well, intellectual property is about ideas and their ownership, and it's basically about the rights of creators to make money from their work.

From playlist Intellectual Property

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An Overview of Agile Development

Get 91% off Hostinger --- https://www.hostinger.com/forrest Agile Development refers to a group of software development methodologies based on iterative development. As a Software Engineer, there's a high chance you'll be using some methodology of Agile Development at work. This video is

From playlist Software Engineering

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How to Work with Wikipedia Sandbox

This is a short video that helps students or editors of Wikipedia to access and edit in the Sandbox of their user account. This was made for the Wiki Edu Project. I do not own or hold copyright over any aspect of the Wikipedia site or its pages. ***There is no audio***

From playlist Wikipedia Education Dashboard Tutorials

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Statistical Rethinking Fall 2017 - week06 lecture10

Week 06, lecture 10 for Statistical Rethinking: A Bayesian Course with Examples in R and Stan, taught at MPI-EVA in Fall 2017. This lecture covers Chapter 8. Slides are available here: https://speakerdeck.com/rmcelreath Additional information on textbook and R package here: http://xcel

From playlist Statistical Rethinking Fall 2017

Related pages

Statistical inference | Automatic differentiation | Laplace's method | Markov chain Monte Carlo | Monte Carlo method | MATLAB | Time series | Limited-memory BFGS | Broyden–Fletcher–Goldfarb–Shanno algorithm | R (programming language) | Hamiltonian Monte Carlo | Probability density function | Statistical model | Stata | Stanislaw Ulam | Forecasting | Variational Bayesian methods