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Here's the public things I've been working in since I joined GitHub. For the topic inference we're using a taxonomy of Open Source we developed last year, but we need to do a bit more work on the classification side. Still, works pretty well for me.

(in case you're interested, widgets available at quine.sh)

Alex Bird's Projects

autograd icon autograd

Efficiently computes derivatives of numpy code.

axplot.jl icon axplot.jl

Plotting utilities for Julia (PyPlot) spun out from my utils package.

axutil.jl icon axutil.jl

A collection of utilities I've developed while working with Julia

batch-shipyard icon batch-shipyard

Execute batch and HPC container workloads on Azure Batch with shared file system provisioning and linking support

examples icon examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

flux.jl icon flux.jl

Relax! Flux is the ML library that doesn't make you tensor

human-motion-prediction-pytorch icon human-motion-prediction-pytorch

Simple baselines and RNNs for predicting human motion. Presented at CVPR 17. This pytorch implementation is based on the original one by the authors

infergmm.jl icon infergmm.jl

Implementation of GMM and various inference methods using GMMs

lpsvm icon lpsvm

(UCL) Project work for large scale SVM solver

matlabparser icon matlabparser

A file to parse called and assigned variables in MATLAB

mtds.jl icon mtds.jl

Implementation of some examples of multi-task dynamical system (in Julia).

nectr icon nectr

nectr: Non-parametric Exploratory Clustering with TURN-RES. This is an R package including an implementation of the non-parametric clustering method authored by Foss, 2002. It was designed for industry analysts who need a fast way to explore a low dimension (p<10) dataset which does not impose a priori assumptions on the structure of the data.

neuralforecast icon neuralforecast

Scalable and user friendly neural :brain: forecasting algorithms.

notes icon notes

generic bin for various notes.

onlineldavb icon onlineldavb

Online variational Bayes for latent Dirichlet allocation (LDA)

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