Here's my modest contribution:

https://blanchardjulien.com/

https://javascriptfordatascience.com

Your feedback is more than welcome!

(Oh and here's "Loulou",my static site generator: https://github.com/julien-blanchard/Loulou)

Glad I ditched Hugo a few months ago.

Great work!

I started with Hugo and ended up building my own static site generator (https://github.com/julien-blanchard/Loulou).

It's been nothing but fun all along. And as you said, building something yourself really makes a huge difference.

https://blanchardjulien.com/

It's just a hobby.

Even my girlfriend doesn't read my posts if I'm to be honest. But the act of writing soothes me, and as a non-native English speaker I feel it's been a great way to improve on my written English.

Also, writing your own static site generator is a pretty fun (and easy) thing to do.

Shameless plug as well: https://blanchardjulien.com/ Static site generator: https://github.com/julien-blanchard/Loulou

Now, this is solely based on my own experience, which of course might not apply to your specific field of work and disability type.

What I mean is, most large companies have a voluntary self-identification form at the end of their job application. And I tend to get a lot more responses when applying for roles where I am invited to disclose my disability.

On a funny note, recruiters always want to confirm that I indeed have a disability, but they can't just reach out and ask "hey dude you sure you didn't click on that button by mistake?".

Instead, they always send this very P.C. email that reads like "Here at [insert company name] we pride ourselves on bein inclusive and bla bla bla. You informed us that you had disability, and we want to make sure that we can accommodate you and make you feel welcome. If you need any special arrangement, please let us know".

To which my response is always "Yes I do have this thing, and no I'm fine thanks".

My disability has fucked up a lot of things in my life, but it's boosted my career.

Over those 4 months I applied for a total of 87 roles for data scientist / analytics engineer. Outcome:

- Ghosted: 49.4% - Rejected: 34.5% - Role cancelled: 3.4% - Interview: 12.6%

That breakdown was consistent across all my former workmates (between 50 to 100 applications before signing a contract), which is largely due to mass layoffs / high competition in the tech sector

Being ghosted is the norm (more on that later)

Avoid recruitment agencies at all cost. Here, they will ghost you for the jobs you apply for, and will then start contacting you for roles you're overqualified for (internships, etc..)

What we realised after a while, from chatting with folks who work in the recruitment field is that if you start getting loads of templated rejection email a few days / weeks after applying for roles, this means that nobody ever read your resume.

Each role we apply for usually receive 100+ applications, and that the recruiter who posted the role is also hiring for a network engineer, a janitor, two junior data analysts, a marketing consultant, a senior project manager, etc..

In other words, they're going to receive several hundreds of resumes, and they won't be able to read all of them. Actually, they'll only read 10 resumes for each role, as is the norm in modern HR.

It seems that most recruiters these days use ATS software to do all of the work for them. Here in Ireland the top ones are "Lever ATS" or "Recruiterbox ATS". Depending on the keywords that the recruiter enters, each resume gets a score. The recruiter then proceeds to open the top 10 applications only, and clicks on a button that sends a templated rejection email to all the unfortunate candidates that didn't make the cut.

Though recruiters usually try and become experts in a specific area ("I'm a tech recruiter", "I'm a recruiter that specialises in finance"), they actually know very little about the jobs that they hire for.

The truth is, 99% of the time, the reason why we get rejected isn't because we're not a good fit for the role. It's because we failed to pass the ATS software filtering process.

I'm a big fan of your work, and as I've learnt a lot from reading your blog posts over the years, I'd be curious to know a bit more about typical use cases for wanting to work with Observable notebooks.

The only reason why I'm using A JavaScript notebook tool (Starboard.gg) is to be able to access cool visualisation packages like Anychart or Highcharts.

Given the hype around Observable notebooks, I feel that I'm missing something.

What makes you decide to start something in an Observable notebook rather than in Jupyter?

Thanks!

I for instance just moved to a company where the data stack is basically OracleSQL and R. And I dislike both. But as _Wintermute pointed out, a whole company / department won't change their entire tech stack just to please one person.

You'll find a ton of public datasets on GitHub [1].

Maven Analytics offers a monthly data analytics challenge [2] that you can enter for free. See their past competitions for some interesting datasets.

As I'm based in Ireland I'll also recommend the Irish Data Portal [3].

[1] https://github.com/awesomedata/awesome-public-datasets [2] https://mavenanalytics.io/challenges [3] https://data.gov.ie/

For context, my team wrote scripts to automate catching spam at scale.

Long story short, there are non spam-related reasons why one would want to have their website show different content to their users and to a bot. Say, adult content in countries where adult content is illegal. Or political views, in a similar context.

For this reason, most automated actions aren't built upon a single potential spam signal. I don't want to give too much detail, but here's a totally fictitious example for you:

* Having a website associated with keywords like "cheap" or "flash sale" isn't bad per say. But that might be seen as a first red flag

* Now having those aforementioned keywords, plus "Cartier" or "Vuitton" would be another red flag

* Add to this the fact that we see that this website changed owners recently, and used to SERP for different keywords, and that's another flag

=> 3 red flags, that's enough for some automation rule to me.

Again, this is a totally fictitious example, and in reality things are much more complex than this (plus I don't even think I understood or was exposed to all the ins and outs of spam detection while working there).

But cloaking on its own is kind of a risky space, as you'd get way too many false positives.

It was, however, one of the most difficult types of spam to detect and penalise, at scale.

Hey everyone!

I started this site during the pandemic, mainly to improve my written English. It's mainly around data science (mostly NLP) / analytics.

I'm trying to publish an article every 3 weeks.

Feedback is appreciated!

Recent articles:

* Exploring POS Tags Co-Occurrence With WinkNLP and Highcharts.js: https://blanchardjulien.com/posts/arcdiagram/

* Create a Simple In-Browser SQL Playground With Pyscript: https://blanchardjulien.com/posts/sql_pyscript/

* Time Series Forecasting With Meta's Prophet: https://blanchardjulien.com/posts/prophet/

* Network Graphs Part I: Python and JavaScript: https://blanchardjulien.com/posts/networkplots/

Though we arguably rely on a lot of Apache products, whatever we use that's internal only is great to work with. Daiq** recently started supporting notebooks, which has been a game changer for us as well as for the teams we work with. Phabricator is great as well, and makes shipping stuff super easy. Only Ben**, the internal notebook solution, I find meh. Especially compared to Google Colab. But the rest has simply been a joy to work with.

For those interested, a former DE made this nice repo that maps internal tools against "real world" products: https://github.com/thijsessens/xmeta2external

Bob Frankston: https://www.youtube.com/watch?v=4BAV69CPXzA Dan Bricklin: https://www.youtube.com/watch?v=Dh0KBkC_21s

I'm slightly too young to have ever used VisiCalc, but that was an interesting read. Thanks for sharing.

Switched from Ubuntu to Manjaro a year ago as Ubuntu updates kept on breaking everything: drivers, issues with Python.

I also quite like the pieces of software that ship with Manjaro. Especially Kate, which I'm now using on my Windows devices as well.