qpsy's repositories
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 ;)
BLNNbook
Bayesian Learning and Neural Networks (jupyter book sources)
clime2
efficient clime
emacs.d
An Emacs configuration bundle with batteries included
example-models
Example models for Stan
greta2
simple and scalable statistical modelling in R
Hands-On-Gradient-Boosting-with-XGBoost-and-Scikit-learn
Hands-On Gradient Boosting with XGBoost and Scikit-learn Published by Packt
HMC_tutor
Just a little MCMC
intro_tidyverse_presentation
Slides of my introduction to the Tidyverse
knitr-examples
a collection of knitr examples
lavaan_
an R package for structural equation modeling and more
practices-of-the-python-pro
Examples and exercises for Practices of the Python Pro from Manning Books 🐍📘
SMMR_Twitter
Mining Opinions, Exploring Trends and More with Twitter
vim
My Vim configuration.
keras
R Interface to Keras
machine-learning-and-simulation
All the handwritten notes 📝 and source code files 🖥️ used in my YouTube Videos on Machine Learning & Simulation (https://www.youtube.com/channel/UCh0P7KwJhuQ4vrzc3IRuw4Q)
py-irt2
Bayesian IRT models in Python
reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
Reinforcement-Learning-2nd-Edition-by-Sutton-Exercise-Solutions
Solutions of Reinforcement Learning, An Introduction
reinforcement-learning-an-introduction
Python Implementation of Reinforcement Learning: An Introduction
tensorflow
TensorFlow for R
tfprobability
R interface to TensorFlow Probability
torchr
R Interface to Torch