Zvi Baratz

https://github.com/google-research/tuning_playbook

New initiative from Google research with the goal of formalizing the process of hyperparameter tuning in DL. Seems to be trending pretty hard (about 1.5k github stars in the last 8 hours alone).
I've been playing around with keras-tuner recently and have definitely felt the need for something similar to this to refer to for numerous decisions. Interesting to see where this goes.

#Google #deeplearning #dl #hyperparametertuning

OK. That's unsatisfying.
I have to try one more thing before I give up on this –

Neuroimagers!!

How much do you care about how your data is managed (i.e., how the raw DICOM, NIfTI, etc. files are organized and distributed)?

Please boost for reach 🙏 🧠 💽
#neuroimaging #data #dicom #nifti #bids #rdm #neuroscience #research

Just in case someone out here finds it useful, here's a link to my #ML for #Neuroscience exercise booklet (made with #JupyterBook ):

https://zvibaratz.github.io/ml_for_neuro/chapters/chapter_01/exercise_01.html

It's probably my last year TAing the class, and I haven't updated it in a while, but there are a couple of (hopefully) useful tutorials in there; particularly exercises V and VI, plagiarized (I mean adapted) from bits of the ISLR and an incredible workshop given by @[email protected] on #NeuroHackademy 2020 (see https://github.com/neurohackademy/nh2020-curriculum/tree/master/tu-machine-learning-yarkoni).