Probabilistic Programming allows flexible specification of statistical models to gain insight from data. Estimation of best fitting parameter values, as well as uncertainty in these estimations, can be automated by sampling algorithms like Markov chain Monte Carlo (MCMC). The high interpretability and flexibility of this approach has lead to a huge paradigm shift in scientific fields ranging from Cognitive Science to Data Science and Quantitative Finance.
PyMC3 is a new Python module that features next generation sampling algorithms and an intuitive model specification syntax. The whole code base is written in pure Python and Just-in-time compiled via Theano for speed.
In this talk I will provide an intuitive introduction to Bayesian statistics and how probabilistic models can be specified and estimated using PyMC3.
Thomas Wiecki is currently enrolled in the Ph.D. program at Brown University where he investigates the neuronal underpinnings of mental illness using quantitative methods like Bayesian Modeling. He also works as a quantitative researcher for Quantopian Inc where he helps building the worlds' first browser based financial backtesting platform.
What is PyData?
PyData.org is the home for all things related to the use of Python in data management and analysis. This site aims to make open source data science tools easily accessible by listing the links in one location. If you would like to submit a download link or any items to be listed in PyData News, please let us know at: firstname.lastname@example.org
PyData conferences are a gathering of users and developers of data analysis tools in Python. The goals are to provide Python enthusiasts a place to share ideas and learn from each other about how best to apply the language and tools to ever-evolving challenges in the vast realm of data management, processing, analytics, and visualization.
We aim to be an accessible, community-driven conference, with tutorials for novices, advanced topical workshops for practitioners, and opportunities for package developers and users to meet in person.
A major goal of PyData events and conferences is to provide a venue for users across all the various domains of data analysis to share their experiences and their techniques, as well as highlight the triumphs and potential pitfalls of using Python for certain kinds of problems.
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