digitalzombie

> You dont make the rules about how someone gets to speak.

I don't have to make any rules. I'm saying how he did it got him fired. If you think how he did it is correct go ahead and do it in all of those tech companies. You think you won't be risking getting fire doing the way he did it?

Whether you like it or not. Just like his memo trying to be slapping hard truth down. I'll give this unpopular opinion down. There is always rules on how to sell your idea and say things especially sensitive matter. If you're going to go blunt about it, don't get mad if you're going to get fire. Actions have consequences. He could have gone about it many ways and if you think his ways is the best go ahead and do it at your company with his memo. I wouldn't be surprise you get fire.

Rules? Ha. I just have to point to what happened to him. He got fire cause his way got him fire. Rules? You think this idealist thought of yours work with people? Try managing people with many different ideas and being blunt all the time.

You're the same as the people that didn't like his memo. You can't handle the blunt truth and got angry.

Also here's a thought experiment. Why don't you use your real name instead of a username handler and post the same thoughts online.

I'd like to see if you act the same way with your real name as a username.

> It is an odd thing that a company can on the one hand become known as the one firing an engineer who tried to open an honest discussion on a hot subject like 'gender discrimination' because that engineer was deemed to lack a moral compass

It wasn't an open honest discussion.

He wrote some memo and it was pass around the Google until some people found out and got offended.

If he wanted an honest discussion he shouldn't be passing notes around like it's highschool. The memo apparently ended up being pass by more and more people. That's not how you approach this or many topics that are sensitive. I think his lack of common sense and clarity screwed him over really.

This is my understanding base on this article:

https://motherboard.vice.com/en_us/article/kzbm4a/employees-...

Gizmodo have the full letter:

https://gizmodo.com/exclusive-heres-the-full-10-page-anti-di...

This is before we even approach this sensitive topic, regardless how anybody feel about it, he have already messed it up from the get go.

Written by the creator of the bootstrap method in statistic.

Bayesian isn't used much in the industry compare to frequentist approach. Likelihoodist is even rarer. I've learned a bit on Bayesian but end up refocusing on time series and survival analysis within frequentist domain. There is waaaay more job posting and people that you work under that are frequentist or more comfortable doing it the old way.

Uh... so the bottom one of the or is CSV 1.1?

How do you define headers? There's no header for the bottom csv version so I have to manually type headers for my data frame?

I got a dataset with 87 obs and ~8700 columns here. I'm not going to manually name those columns. What's the solution?

They recently added terminal to RStudio. I'm so happy not switching between two app Iterm2 and RStudio.

> This trope is getting old. Variations include "Go is only popular because Google spends millions marketing it!".

I chose Angular.js because of google actually. And then Google did me dirty with Angular 2.

Corporate sponsorship is actually a huge driving for my decision and many company too.

Having a big company is a good indicator of success and it says that that programming language will have a stable contributors. Google also are using Go so they also have a stable programmers within the ecosystem.

Getting developers to adopt a tech and be in it is hard. Google have bunch of their dev in it and which increase the chances of these dev will present and talk in meetup to evangelicalize others.

I disagree. They can do whatever they want because it's passion driven.

If people finds the new language wonderful they'll choose to spend their time there and to create their own community around it.

It's their free time and they have every right to choose how to spend it.

Also with RPC, the apache project arrow, etc... there'll always be people out there will bridge community.

Also is this really a problem? Programming language fragmentation? I've seen front end javascript frameworks fragmentation everywhere and they're fine with it. And the solution on the horizon are standardization such as web component (via w3c). These frameworks converge toward web component and now it's getting standardize. I'd argued that because of the fragmentation we actually know what we want to standardize and it also pushed for it.

If there weren't any fragmentation I'm not entirely sure if web component would ever be standardize.

> In the mid-1980s, just as the Aids crisis peaked and US scientists discovered the virus that caused the disease was borne by blood, American drug companies knowingly sold HIV-tainted blood products in Asia.

It wasn't just an American company, there were actually two companies, Bayer (German) and Baxter (American). Baxter have a history of very shady things, I'm surprised they're around. I wish the author cite the quote or more clear on that part.

https://en.wikipedia.org/wiki/Contaminated_haemophilia_blood...

https://en.wikipedia.org/wiki/Baxter_International#1996_Japa...

> statistics is a three year long grueling applied maths degree, and condensing it to three weeks is silly.

I agree. I was in a very prestige organization and they didn't know what a statistician really do and just hired CS machine learning PHDs. Even those people don't even know what statistician does. One person gave me ISLR when I ask for advice to get hire at this prestige place (I did an equivalent of this over several graduate courses in statistic program).

Another person proudly told me that in his project, he was using GLM stating he knows GLM. I asked what was the link function and that person stated he didn't know and it's somewhere in the code...

I've since then double down on statistic and will be going into Biostatistic field instead of data science. It feels like there are a lot of impostors especially in start ups and government organizations in data science. I have no clue why but there is just this culture in tech industry that have made me left it for better field. I've intern in the biostat field it is much better. CNN and other have listed with high quality of life.

Again the main point of my post was the FUD about Oracle and opensource is not base on nothing. Oracle's past actions toward open source shows this. You're welcome to disagree with counter argument, I would like to learn and be wrong if I am wrong (or missing something).

But I failed to see how your personal opinion on fork on java and ecosystem have to do with my original post on Oracle's FUD and past action against open source.

If none of your cases you've bought in this argument/debate is toward this topic then I think you're pushing a narrative and being dogmatic toward Java. I have no beef against the language but I am wary of Oracle. I'm merely refuting/adding toward the comment of the post I'm replying to.

I remember exactly what Sun Microsystem did it breached and been waving a carrot in front of Apache about TCK. What's stopping Oracle from giving TCK now? Also that's exactly not the whole truth you're presenting.

https://blogs.apache.org/foundation/entry/the_asf_s_position...

> Unfortunately, Sun breached the JSPA in 2006 by licensing the Java SE Compatibility Kit under terms inconsistent with its prior representations to ASF and its obligations under the JSPA, and incompatible with ASF's development of Apache Harmony. ASF urged Sun to honor its agreements, but after Sun persisted in its breach for a year, ASF withdrew from the JCP. At the time, Oracle supported ASF's position that Sun was in breach of the JSPA. But after acquiring Sun, Oracle adopted Sun's policy, disregarding the limits of the JSPA that formed the basis for ASF's participation in the JSP and acceptance of the various TCK licenses.

> Some people easily forget or act as if past actions/history aren't a metric, while others forget who actually did them in first place.

Choosing a video to support half a truth or a part of timeline doesn't mean anything.

Here's another source:

https://arstechnica.com/information-technology/2010/12/apach...

> The heart of the issue is that Apache can't certify that its open source Java implementation—called Harmony—conforms with the Java language standards because Oracle refuses to supply the necessary test suites under a suitably open license. Oracle's position on the issue falls afoul of JCP policies, which stipulate that standards and other relevant materials must be freely redistributable and made available under terms that are conducive to enabling third-party open source implementations.

You're deflecting any and all of Oracle's action toward Google should have bought it and well Sun did it first. That's a terrible argument to counter my point of Oracle past actions being terrible toward open source. The "google should have bought Java" is such a hand wave especially when Google did a clean room implementation of Java and involve the issue of if API is copyrightable (https://en.wikipedia.org/wiki/Oracle_America,_Inc._v._Google...).

It's not like they did a hostile take over, sued Google for API, and dump their failing project to apache or anything. Or refused to give TCK to apache harmony project. Or hell even tons of anecdote of Oracle buying out services just to bilk people with more money until it rot. Or have a clause for anybody using Oracle DB cannot benchmark.

I feel people easily forget or act as if past actions/history isn't a metric to judge a company by. You can't predict the future with your feeling you can only do it via past data/actions. That or is it tribalism dogma that their bread and butter tech is being harshly criticize?

> will be cleaning sewers until death comes.

What does this mean? Is this a prison punishment?

You're the reason why I inherit project that uses only ES and then end up doing relational schema in ES because they didn't use relational database in general.

If you had to choose between PostgreSQL or ElasticSearch then you have no idea what you're doing.

We, the USA, is not going to have any friends left... Seems like Trump is pissing off Canada, Mexico, NATO, and EU.

> why don’t we split the data sets to train and update the coefficients and automate the process.

What you just stated is just a pipeline. You can just split the data and train it and automate with tree ensemble that aren't boosting that is if you're talking about doing in parallel.

If you're just saying split and do as batch process in different time interval you can do that with nonparametric bayesian.

CS contribution in creating Deep learning and having it be the best accurate algo for certain data domain is pretty nice. But again Stat care a lot more than prediction.

Your CS term for parametric is not quite 1 to 1 with statistic usage for parametric.

Also what you're describing is very similar to Bayesian statistic.

> But more importantly, LSTMs and neural networks are very much parametric - their success come from the advances in computing and optimization that have enabled estimating these parameters in very complicated model structures.

Which for statistician is basically blackbox and nonparametric since you have no idea what the distribution is dude and there is no assumption of a distribution. Hence nonparametric statistic which is the answer to your question you've asked for.

> The ancient greeks rejected ( or ignored ) irrational numbers too

They didn't rejected it for computational reason. They rejected it because it didn't fit in their framework of how number works.

That's the whole point of the evolution of math that culminated into the subject of real analysis.

If that wasn't the point of why you brought the greek up then it doesn't make sense why you bought it up other than the main topic of the Chinese, computation, etc...

Bro I feel the same way Kubernetes is so fragile.

Docker have gone along way but Kubernetes they need more and more version. I feel as I get older I'm more incline to wait a few version for the bugs to be fix and the api to be solidified. The majority of the software out there that come out with version 1 is just marketing to get people to adopt it and they work out the kink as they go on.

Trying to walk on a rope is pretty hard balancing act.

I do want to give a personal view and constructive criticism but any intentional and direct attack toward another domain is not my intention.

I think statistic is very well equipped to do just data analysis. The discipline have many weaknesses I do acknowledge that but I don't believe data analysis is one of it when it is the core tenet of what statistic is.

I believe data science is too new and is still trying to find it's standing. Also it seems like a jack of all trade and a master of none discipline. I don't believe the discipline can be a master of everything including data analysis with all other things it's trying to incorporate.

My critique is that for the original post is that there is already a field for data analysis. Just for it, for a century now, it's named statistic.

ML/DS is a new breed that is more than just data analysis. Because of this they can do many things but I don't believe they are an expert at any one thing. Which is fine. But I do understand that this discussion is sensitive since people within the DS/ML since that is how they make money and earn a living.

I agreed, I didn't want come off as a disgruntle statistician and list the weakness of Python.

But you're right. I find most Springer, CRC, etc.. books are in R with accompanying R packages. Shumway & Stoffer Time series book comes with the R astra package. Andrew Gelman Bayesian create Stan and their target was R first (rstan). The Sanford people who created lasso and elasticnet created glmnet. The thought that the creators or experts of these subject wrote a book or research paper and then also publish R package to accompany it is reassuring.

When it comes to just data analysis, it seem like R is pretty good or better than Python. I think Python is much better for ML stuff such as deep learning and also it seems like Python have better NLP support. Arguably Stanford is very good with NLP and they publish their tool in Java.

> In my experience, all statisticians can do the first, almost none can do the second.

I think a phd statistician can do this.

Master statistic does not touch upon field and measure theory in statistical inference so many questions get unanswered. But I suspect you may be correct.

I view chisq as a statistical distance for most of my encounter and learning.

I think we're talking about different roles.

I'm coming at it from just a modeler role and it seems like you are stating more of a full stack within the data science. I took OP remark as if it was just within data analyst in term of analysing the data and not including turning it into some kind of application.

As for Python, time series isn't as good in python. I do agree that Python production is good. But I don't believe Python have better analysis packages. I'm in the camp of using programing language for their strength and using Apache Thrift or whatever to tie everything in.

I've seen them do random forest on temporal data.

They tried to fix it with PCA.

> why can't data science simply be about applying the scientific method in the realm of data analysis?

That's what a statistician do.

I've seen these ML and Datascience people. And the majority the time how they tackle data is radically different from statistician and is more of an art than a science compare to what statistician does.

But this could be my bias opinion and just some small data sample from personal experiences.

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Actually my last day of internship I've met a few statistician interns some of them are from Cal (UCBerkely) and they came to the same conclusion (we have a lot of complaints). The ML/DS group is really just doing black magic (nicest way of putting it). I wish statistic is better at marketing. Oh well.

> What is classless JavaScript?

Sounds like old school javascript. Either just functional programming or prototype inheritance.

I don't get your statement. But to clarify I was talking about how the crowd in RoR have a high uptick on vim editors. I was reminiscing on the old days of RoR that may have contribute to some more people adopt Vim.

A casual google shows this including a poll in 2014: https://www.sitepoint.com/editor-rubyists-use/

There's even a quora question too: https://www.quora.com/Why-do-so-many-Rubyists-use-VI-M

And a plausible answer "Why rubyists went with vim over emacs could stem from the popular rails.vim plugin from Tim Pope."

> How did Vim become so successful?

I recall the early days of RoR crowd were pushing for Vim too. It was hipster in term of adopting new and awesome things and RoR crowd really push some new things. This was when the editors war was still a thing.

Preemptive is pretty nice. You can have a for loop that runs forever and not take over.

It does processes nicely they're green thread iirc very fast to create.

Clustering is built into it with security.

It's built for soft real time so reliability is pretty nice much more battle tested than perhaps JVM.

It's not own by Oracle is a big deal for me.

> Here is a phase 3 that succeeded and failed. Clearly it works.

That's not clearly works. Quantifying works/succeed with statistic is how you know it clearly works because it's statistically significant. Other wise your clearly work statement is just your opinion and the opinion of a drug company trying to make money.

If it fail and succeed in phase 3 then it's not clear at all if it works.