Are there any practical Pytorch examples? Say my network training time is 12 hours, I wonder how beneficial this would be for hyperparameter tuning over just simple grid/random search? Or would I instrument my network in a way to iterate over hyperparams faster than at every epoch/run?
> ...there’s little hope of sharing and growing the world’s knowledge if those doing so ... cannot trust that their information will remain private.
Here's a crazy idea, circa 1990's: don't store their personal information! Allow people to browse Quora without using their real names. I'm very happy I deleted my Quora account when I did.
I just built a test site with Netlify + GitLab. Why must I give it full access to all of my GitLab repositories? I just want to deploy 1 repo. Seems like that opens up unnecessary possibilities for a security breach.
I'd highly recommend folks create a tldr page for their CLI app. Add 4-8 examples to cover 80%+ of the most common use cases. -h flags, readmes & man pages can cover the other 20%.
Python 3.7 is supported if you build master from source. But that can be a lot of work and though it may solve your TF problem, it may create other problems with other Python packages.
In my experience conda is the way to go for setting up your environment. I did not have great luck with pyenv, YMMV.
I don't know about WSL. Maybe setup a dual boot with Ubuntu on your system?
> The point will come when not regularly wearing one of these devices is considered hazardous to one's health
I 100% agree. I think we are on the cusp of the "cyborg" era, like it or not. Humans will wear health tracking devices at all times. Already 10M+ do, from basically 0 a decade ago.
Personally the sleep tracking and heart rate data from wearing my bands since 2014 led me to a diagnosis and fix for a number of health issues.
But the real promise lies ahead, as new and better sensors are engineered. In addition to helping with traditional health issues, devices will increasingly allow the conscious part of your mind to have real-time self-awareness of the biological factors going on that influence your thoughts and decisions and answer questions like these:
- Did you say "no" to that thing because it was the right decision or because your blood glucose level was so low?
- Was your high productivity level today a fluke or influenced by the high caffeine level in your system?
- How "tired" are you really?
Some people might not like it, but I don't know if they'll have a choice. Not taking advantage of these technologies would put them at a disadvantage in school, work, sports, and perhaps all other areas in life.
I think that moment is more like 10-20 years out, but otherwise agree with you.
I recently was looking to see where Samsung watch's health team was in the U.S. As far as I could tell there isn't one. I could be wrong, but that would seem to be a disadvantage compared to Apple/FitBit/Garmin/etc, since the more health focused these apps get the more they'll have to work with the FDA, insurers, hospitals, etc.
In 2020 alone we will collect more high-dimensional health data than from the beginning of history to the present day combined. Given the improving sensors on the wrist generating high-dimensional data (heart beat, ecg, perspiration, blood oxygen, motion, vibration, body temperature, etc), and a sample size of 100M+ people, is it not possible that there is some previously unknown signal in there that could be detected by deep learning?
I'm not saying there is, I just wonder if heart attacks might cause some discernible but very complex pattern visible in high-dimensional data that we haven't discovered yet, or if there is just too much physical distance between the wrist and heart to drown out all signal.
The "health" tests were of dubious accuracy, but as a long-time customer I always thought their warnings and caveats about those tests were enough. I was sad when the FDA made them stop. However, since the FDA action and the recent restoration of the health tests the product has improved, so I guess the FDA's move was was for the best.
The genetics component has always been terrific. I've had friends uncover surprises, like one who unraveled a mystery about an undocumented and unmentioned great-grandfather, who they found out was from a different continent and shunned by the family.
Even though I work in the 'omics field, I'm still amazed every time I get an email from 23andme that a sibling or cousin has joined, with them determining that based on nothing but some spit.
I think it's a very exciting company to watch and it's just getting started.
> a single individual could need multiple sequences stored.
And multiple sequences could be hundreds, thousands, or more. Example: single-cell RNAseq pipelines that generate sequences for 10k cells at once.
Perhaps in the future--as tech improves--the devices themselves might be equipped to run more real-time in memory QC and emit less--but more accurate--data? I believe this is somewhat how CERN does it, where they only record a filtered subset of the data that comes in.
I agree but I would say mix the tool teaching with fundamentals. Let them bang away for an hour trying to make some simple change to their tool script, and then show them the principle that had they known about they could have solved their problem in 30 seconds.
Stoke in them the desire to invest regular time learning the fundamentals.
This is an anecdote but my guess is a lot. I was a software engineer for a decade and recently transitioned to a bioinformatics job. A cursory look at many of the repos that supplement published papers (even in top journals like Nature), will show you that there are often no tests or type documentation of any kind and quite often you'll find bugs when you use packages with your own datasets. So to the OP I would recommend either teaching fundamentals first or concurrently--but don't skip fundamentals!
I feel the same way. Prettier is a dream--instant speed, great output and 100% reliability for over a year.
So far black seems great. I just ran it on some existing Python packages and it was fast and the output was correct. Still need to try the editor plugins but very excited so far.
Now, if only someone would lead a similar project for R. :)