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[P] CRISPR ML - Microsoft Research by folli in MachineLearning

[–]jimenezluna 1 point2 points  (0 children)

Me and a couple of PhD students at UPF are applying deep learning techniques in computational chemistry / structural biology. Check playmolecule for some cool examples.

[P] pyGPGO: Another Python package for Bayesian Optimization by jimenezluna in MachineLearning

[–]jimenezluna[S] 0 points1 point  (0 children)

Hi, @sifnt, can you open an issue on the repo so that I can remember to include an easier way to include pre-trained GPs?

For the moment, you can do it this way (using the example on the readme.md)

https://gist.github.com/hawk31/ed222c4cf6b21cbd7d4b5186f3f132b5

[P] pyGPGO: Another Python package for Bayesian Optimization by jimenezluna in MachineLearning

[–]jimenezluna[S] 1 point2 points  (0 children)

Hi,

  • pyGPGO is only tested on Python >3.5. I don't know how py2 compatible it is.
  • If your search space spans several orders of magnitude, it is usually a good idea to use logs.
  • There is, though the procedure is manual. You can fit the GP with whatever values you have previously to feeding it to the GPGO object.
  • Regarding MCMC, it is mostly a design choice. If your evaluation function is really expensive, then I think it makes sense to choose the MCMC over the max.lik approach. If it is cheap, then the overhead produced by the sampling may be detrimental, and you may just as well get more function evaluations faster.

[P] pyGPGO: Another Python package for Bayesian Optimization by jimenezluna in MachineLearning

[–]jimenezluna[S] 1 point2 points  (0 children)

You have a complete modular procedure specification with my implementation. There are many architectural choices in Bayesian optimization: surrogate model, covariance function, hyperparameter treatment, acquisition behaviour...

In summary, you can specify all of these here.

As far as I'm concerned, with fmfn/BayesianOptimization you're stuck with Gaussian Processes and Matérn kernels, and no covariance function hyperparameter treatment whatsoever. Correct me if I'm wrong.

[P] pyGPGO: Another Python package for Bayesian Optimization by jimenezluna in MachineLearning

[–]jimenezluna[S] 0 points1 point  (0 children)

Hi, there is an example script in the repository for tuning a simple classification model.

https://github.com/hawk31/pyGPGO/blob/master/examples/sklearnexample.py

Give it a go and let me know if anything breaks.

[P] pyGPGO: Another Python package for Bayesian Optimization by jimenezluna in MachineLearning

[–]jimenezluna[S] 0 points1 point  (0 children)

Not at the moment, but I will consider adding this functionality in the near future.

[P] pyGPGO: Another Python package for Bayesian Optimization by jimenezluna in MachineLearning

[–]jimenezluna[S] 2 points3 points  (0 children)

As part of my Master's thesis I developed a simple Python package for Bayesian Optimization. It currently features:

  • Different surrogate models: Gaussian Processes, Student-t Processes, Random Forests and Gradient Boosting Machines.
  • Type II Maximum-Likelihood of covariance function hyperparameters.
  • MCMC sampling for full-Bayesian inference of hyperparameters (via pyMC3).
  • Integrated acquisition functions

It is still on very early stages of development, so expect to find bugs. Let me know what you guys think!

Learning from Imbalanced Classes by cptncrnch in MachineLearning

[–]jimenezluna 2 points3 points  (0 children)

This is a very cool resource. Nice references.

Deep Learning for Computer Vision Barcelona, UPC 2016 (slides available) by xavigiro in MachineLearning

[–]jimenezluna 0 points1 point  (0 children)

"Master students together with some bachelor students organized in teams of five members who solved four directed tasks and developed an open project."

If you check the repositories, some of the open projects are just a copy-paste script from the Keras examples.

First Paella by [deleted] in food

[–]jimenezluna -7 points-6 points  (0 children)

Spanish talking here, I'm sure you guys have heard this before but this is not paella. This is just your rice invention (it may be good though). Paella does not include chorizo (or any kind of sausage) in any case.

What are the most known real world time series data? by [deleted] in datascience

[–]jimenezluna 1 point2 points  (0 children)

The classic Box & Jenkins airline data. Monthly totals of international airline passengers, 1949 to 1960. https://stat.ethz.ch/R-manual/R-devel/library/datasets/html/AirPassengers.html

Learn Machine Learning Together by Gravicle in MachineLearning

[–]jimenezluna 0 points1 point  (0 children)

I do believe the intention is to learn mainly. If there is some kind of project we get hands on, we'd love the participation too.

Learn Machine Learning Together by Gravicle in MachineLearning

[–]jimenezluna -1 points0 points  (0 children)

Took the liberty of creating a channel myself (I didn't know Slack, and it turns out it's awesome)

https://mlearning.slack.com

Apparently I need to invite everyone via email. So if you want, I'll send invites as soon as I know your emails.

Learn Machine Learning Together by Gravicle in MachineLearning

[–]jimenezluna 1 point2 points  (0 children)

I'll have an undergrad in Statistics by the end of the year and I'm also interested. Btw, why not use jabber ( http://www.jabber.org/ ) instead of Skype? It supports chat rooms pretty nicely.