Probabilistic Programming & Bayesian Methods for Hackers (Version 0.1)
PyMC3 is a Python library for programming Bayesian analysis . It is a fast, well-maintained library. The only unfortunate part is that its documentation is lacking in certain areas, especially those that bridge the gap between beginner and hacker. One of this book’s main goals is to solve that problem, and also to demonstrate why PyMC3 is so cool.
We assign them to PyMC3’s stochastic variables, so-called because they are treated by the back end as random number generators.
Previously, I used MATLAB for my research. I’m familiar with the development environment in the MATLAB IDE.
Now I’m trying to migrate everything into Python, and of course there rises many problems. This blog is used to track all my problems and, more importantly, solutions.
One day I run across this web page of Software for machine learning but sadly find that most links are not available anymore. So, I decided to make a copy and try my best to maintain the sources. The machine learning is a big area, so this page may be only useful to researchers in my area (aerospace engineering), who usually have limited computer science knowledge than a CS professional researcher.
I collect some open source aerospace softwares in this post. For present, my focus is on orbital and attitude dynamics, but also include some remote sensing data handeling and analysis.
Suggestions, recommendations, and comments are very welcomed.
2019-06-11Gaussian Process is a plural noun describing a random function with assumed Gaussian joint distribution
Again, I run into the question that “what’s the difference between GP and GPs”? Here, GP is Gaussian process while GPs is Gaussian processes. So you see the difference?
In this post, I decided to solve this confusion (a better words? puzzle? bewilderment? perplexity?) once and for all.