Have error messages improved? I remember trying it few years back but the error messages made it hard to debug. Is it due to use of JVM? Sorry for my lack of knowledge since I rarely program in JVM based languages.
I use R a lot but I still prefer Javascript libraries for interactivity. Javascript libraries feels lot more smoother than something like webR. Having said that, it is impressive that R is able to transcend in the interactivity with just internet browser.
Classical stats is still bread and butter for lot of smallish dataset in clinical datasets.
It is hard to do machine learning or even regression on some very preliminary data. Metadata is tough to collect and harmonize so it becomes hard to integrate specially with human studies with rare diseases.
R data science people generally come to data science field from life science or stats field. Python data science people generally originate from other fields that are mostly engineering focused. Again this may not apply to all the cases but that is my general observation.
Recently I am seeing that Python is heavily pushed for all data science related things. Sometimes objectively Python may not be the best option especially for stats. It is hard to change something after it becomes the "norm" regardless of its usability.
I am not really familiar with Go but I wonder where it would be without Google's support and maintenance. I have no doubt it is a solid language with some really smart people in programming language design behind it.
It is so much easy to release programming language but so much difficult to maintain and curate it over time.
It feels as if it was created for ticking some checkboxes. Not sure what is the motive here. Having said that, personally it has not created any major issues for me though.
Smartphones feel like a saturated devices in terms of functionality. Way too many things depend on it and interface is riddled with so many functions.
I miss the very first iPhone. Perhaps it was the novelty at that time. It was slower and had way less functionality but easy to use.
I guess it is hard to balance functionality and ease of use. It is becoming a hodgepodge of apps/things. Sorry to echo the sentiments expressed here.
Currently evaluating UUIDv7 as primary key for some inventory origin. I think it should be ok to use it for such use case since it will indicate the time of creation? Any thoughts?
Phone usage is getting more intense as we move from mere passive consumption to having them as creative (compute) device. "Heat" is sort of reflection of that.
I want to see more optimization to reduce the heat from both hardware as in this case and in software side as well. I guess it is easier to show enhancements about hardware made to address something such as heat or processing but comparatively difficult or abstract to show software optimizations?
Granted I have the M4 Mac Studio, but it seems to be running just fine in my 3-4 days of use so far. Also the OS seems to be as stable as last version. I wonder if there are any issues besides the visual glitches and slowness? Also over the years I have found MacOS generally stable. I hope they will address the issues over time.
On the side note, I actually miss Snow Leopard release and in general miss the "Skeuomorphism" in all the software I use.
I love R and dplyr. It is very readable and easy to explain to non-programmers. I use it almost everyday.
Not exactly on the topic,I am having difficulties debugging it. May be I need to brush up on debugging R. Not sure if there is a easy way to add breakpoint when using vscode.
My command to backup selected file using Tarsnap.
find /Users/xyz/Analysis -type f \( -name '.pdf' -o -name '.docx' \) -print0 | tarsnap --dry-run --no-default-config --print-stats --humanize-numbers -c --null -T-
This command file files ending with docx and pdf to back with tarsnap. The "-" following the "-T" option allows to pass the name using std-in via find command
Just a shout out to Sublime Text. My first text editor that I have used for serious work. Even though I have moved to Vscode, it is my go to open text files in GUI. It rarely fails me.
If sampling time is effecting mice, good luck with Human Studies. It is not easy to get human gut microbiome samples in clinical trials especially when they are already suffering from disease.
Even with longitudinal studies, patients can skip donating samples. Making it difficult to compare. Also diet (big factor) and genetics can impact your microbiome.
Having said that, I am big fan of longitudinal microbiome studies with good metadata collection such as time of sample collection, Bristol stool scale, and diet(this is very difficult to quantify).
Mostly using Zotero for saving snapshots of webpage. Saving webpage is getting more and more difficult as it approaches the functionality of the desktop application.
Somewhat agree but sometimes there is need to change/filter the data that goes into making the chart which is only realized after plotting it. Combining data and the figures into one "pipeline" makes it easy to iterate especially with exploratory data analysis.
Regardless, this comment made me think about my general workflow which is usually combined. Appreciate this comment.
Not an expert at all. But I think gist of the video is that GPU size relative to other component has increased. Plus they rearranged some of the "furniture" to accommodate that increase.