New post on using Dask and ITK for large scale image analysis.https://t.co/qybJmqLwh3
— Dask (@dask_dev) August 9, 2019
We give a full example for deconvolution, and outline challenges and ongoing work.
New post on using Dask and ITK for large scale image analysis.https://t.co/qybJmqLwh3
— Dask (@dask_dev) August 9, 2019
We give a full example for deconvolution, and outline challenges and ongoing work.
I just reread Breiman’s “Two Cultures” after many years. It remains an absolute gem of a paper, easy to read with minimal equations. And it’s probably even more relevant today than when it was written in 2001. If you haven’t read it, you should: https://t.co/W3If8b0Mlm
— David Smith (@revodavid) August 9, 2019
A question I get from time to time is how to convert a pretrained TensorFlow model in PyTorch easily and reliably.
— Thomas Wolf (@Thom_Wolf) August 9, 2019
We're starting to be quite familiar with the process so I've written a short blog post summarizing our workflow and some lessons learned 👇https://t.co/d8ZMs30nGq
"Because You Can't Run, You Can't Hide: Some Musing on API Design" a great talk from @dontusethiscode from PyData London 2019https://t.co/9dmmal7Mt1
— PyData (@PyData) August 9, 2019
Don't forget to subscribe!
Are you a TensorFlow.js n00b? @dweinberger is!
— TensorFlow (@TensorFlow) August 7, 2019
He's using machine learning to build an app that tags images. He says that prepping data requires thinking like an ML system, which is difficult because machines don't "think" like us.
Learn more ↓ https://t.co/xE7wocGRSV
Just about to kick off the BigQuery Machine Learning workshop. Come hang out and train (and serve!) some models with us. 🤓💻
— Rachael Tatman (@rctatman) August 7, 2019
📓 Tutorial notebook: https://t.co/UCwItIynvQ
📓 Exercises: https://t.co/DIxNuVumVz
📹 Livestream (starting @ 9:00 AM Pacific): https://t.co/Y0ZDTyCvqp
how cookies work pic.twitter.com/OJyLAj0Xp5
— 🔎Julia Evans🔍 (@b0rk) August 6, 2019
Statisticians say the darndest things. E.g., why does nonparametric mean hugely parametric? Regression means numeric prediction? Why does L1 Lasso reg constraint look like ridge and L2 Ridge constraint look like lasso? Enjoy my fun translations :) https://t.co/DrRLA0K5hS
— Terence Parr (@the_antlr_guy) August 6, 2019
Softmax Normalization https://t.co/eZ2bbpDzwV pic.twitter.com/DPBCHgKSFu
— Chris Albon (@chrisalbon) August 5, 2019
Excited to be presenting on Real-World Bayesian Optimization at the #KDD2019 Workshop on Data Collection, Curation, and Labeling for Mining and Learning!
— Yisong Yue (@yisongyue) August 5, 2019
Talk is at 8:05am on August 5th:https://t.co/Jqy0mFZkRR
Slides: https://t.co/njRJBOVxSs pic.twitter.com/ALYayOKWdm
Docker Packaging Guide for Python https://t.co/rCvUFm0KJu
— PyCoder’s Weekly (@pycoders) August 4, 2019
I've taken 7 of these, and I strongly agree with the recommendations in all cases.
— Jeremy Howard (@jeremyphoward) August 4, 2019
(I don't agree with the order, for most people - I'd leave the 1st two until you've become a good practitioner, unless you're extremely patient or are very theory-driven.) https://t.co/cRbTIJpdLI