Dear all,

Just a quick introductory message as requested for new group joiners. I'm a 
Research Scientist with ML Python coding experience in academia and 
industry.

*Python familiarity*: 8 years of programming experience.
*Mathematical education level*: PhD in computational neuroscience. 
*Expertise*: machine learning, computational neuroscience, probabilistic 
modelling.
*Algorithmic interests*: Bayesian methods, deep learning, neuroscientific 
architectures.
*Familiarity with SAS/CAS*.: theoretical research )(cf. engineering 
applications).
*Familiarity with SymPy*: rudimentary.
*Other relevant information*: I am interested in combining the capability 
of computer algebraic systems (such as SymPy) with network analytical 
packages (such as NetworkX) to build directed graphical model (a.k.a. 
belief/causal network) architectures for deep Bayesian inference using MCMC 
and variational Bayes.

I look forward to experimenting with SymPy!

Kind regards,
Gary.

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