Pinned Repositories
1on1-questions
Mega list of 1 on 1 meeting questions compiled from a variety to sources
buffersort
Provide a variety of sorting algorithms that operate in-place on types that implement the Python buffer protocol.
diy-regression
With nothing other than ANSI C (c99), here's some code to perform OLS regression and report coefficients and their t-stats.
dockerfile
Parse a dockerfile into a high-level representation using the official go parser
dockerphile
Programmatically create and manipulate Dockerfiles.
learnmeahaskell2
Practice Haskell problems
learnmeapostgres
A bouquet of random PostgreSQL trickery.
llvm-trapezoidal
A reference project on implementing algorithms directly in llvm IR and via llvmlite in Python.
nn4params
Learn to predict regression coefficients from data
simpleRNN
Example RNN for text generation from "Deep Learning With Keras" by Gulli and Pal (Chapter 6).
spearsem's Repositories
spearsem/buffersort
Provide a variety of sorting algorithms that operate in-place on types that implement the Python buffer protocol.
spearsem/1on1-questions
Mega list of 1 on 1 meeting questions compiled from a variety to sources
spearsem/learnmeapostgres
A bouquet of random PostgreSQL trickery.
spearsem/nn4params
Learn to predict regression coefficients from data
spearsem/simpleRNN
Example RNN for text generation from "Deep Learning With Keras" by Gulli and Pal (Chapter 6).
spearsem/diy-regression
With nothing other than ANSI C (c99), here's some code to perform OLS regression and report coefficients and their t-stats.
spearsem/dockerfile
Parse a dockerfile into a high-level representation using the official go parser
spearsem/dockerphile
Programmatically create and manipulate Dockerfiles.
spearsem/learnmeahaskell2
Practice Haskell problems
spearsem/llvm-trapezoidal
A reference project on implementing algorithms directly in llvm IR and via llvmlite in Python.
spearsem/monad-challenges
A set of challenges for jump starting your understanding of monads.
spearsem/pymc3
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
spearsem/taurus
Automation-friendly framework for Continuous Testing by