Thomas Wiecki

financial-analysis-python-tutorial. Financial Analysis in Python tutorial

WhileMyMCMCGentlySamples. my blog

covid19. Analyses about the COVID-19 virus

CythonGSL. Cython interface for the GNU Scientific Library (GSL).

pymc3_talk. Bayesian Analysis in PyMC3.

datascientist_tutorial.

pydata_docker_jupyterhub. Docker container with a PyData stack and JupyterHub server

replicate_google_trends. Replication of "Quantifying Trading Behavior in Financial Markets Using Google Trends" by Preis et al 2013

ipython_nb_cluster. Scripts to launch IPython parallel on a cluster and run an IPython Notebook to run the analysis.

mpi4py_map. mpi4py_map provides a simple map() interface to mpi4py that allows easy parallelization of function evaluations over sequential input.

twiecki.github.io-old. Personal blog raw files.

Bayesian-Modelling-in-Python. A python tutorial on bayesian modeling techniques (PYMC3)

awesome-bayesian-statistics. A repository for collating all the resources such as articles, blogs, papers, and books related to Bayesian Statistics.

pydata_ninja. The Path of the PyData Ninja

zipline_in_the_cloud_talk. IPython NB slides of my PyData'13 talk.

pymc-in-browser. Demo of running PyMC in the browser using PyScript

stopsignal. Hierarchical stop-signal model (Matzke et al, 2011) that allows estimation of SSRT and SSRT variability.

hqlearn. Hierarchical Bayesian QLearning models

zipline. Zipline, a Pythonic Algorithmic Trading Library

pydirect. Python wrapper to the DIRECT global optimization algorithm (forked from http://code.google.com/p/pydirect/source/browse)

PyData2014-Berlin. Networks meet Finance in Python - July 27 2014

Probabilistic-Programming-and-Bayesian-Methods-for-Hackers. aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

edward. A library for probabilistic modeling, inference, and criticism. Deep generative models, variational inference. Runs on TensorFlow.

pyscript. Home Page: https://pyscript.net Examples: https://pyscript.net/examples

covid-model. Jupyter Notebook

microarviz. Exploratory analysis of Bayesian models with Python

pyemergent. Specify, run, and analyze emergent experiments in Python.

multilevel_modeling. Tutorial on multilevel modeling, using Gelman radon example

IPython-plotly. A collection of IPython notebooks that feature Plotly graphs. Content moved to https://plotl.ly/ipython-notebooks/

Bayesian-data-analysis-with-PyMC2. Bayesian data analysis with PyMC(2)

pymc.io. PyMC project website and blog!

numba. NumPy aware dynamic Python compiler using LLVM

pymc. Bayesian inference in Python

hddm. HDDM is a python module that implements Hierarchical Bayesian parameter estimation of Drift Diffusion Models (via PyMC).

aesara. Aesara is a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays.

param_recovery. Suite to test whether your model can recover parameters. Experimental.

pytensor. PyTensor is a fork of Aesara -- a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays.

bg_inhib. Simulation code for the paper "A computational model of inhibitory control in frontal cortex and basal ganglia."