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pablobaz

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tidyfirst.substack.com 7mo ago

The Bet on Juniors just got Better

pablobaz
1pts0
www.highcharts.com 3y ago

Highcharts GPT: Create real charts with simple prompts

pablobaz
1pts1
github.com 3y ago

ArcticDB: A high performance, serverless DataFrame database

pablobaz
2pts0
medium.com 3y ago

Introducing ArcticDB: Powering data science at Man Group

pablobaz
3pts1
www.nextplatform.com 3y ago

Compute is easy, memory is harder and harder

pablobaz
9pts0
www.rte.ie 3y ago

Aer Lingus cancels all flights from Dublin to Europe

pablobaz
3pts0
www.man.com 4y ago

Bending Moore's Law: Single-Core Stagnation and the Cloud

pablobaz
2pts0
medium.datadriveninvestor.com 5y ago

Battle of the Python Dashboarding Giants: Streamlit vs. Dash vs. Voilà vs. Panel

pablobaz
38pts8
www.man.com 5y ago

We Rewrote Our USD30B Asset Management Platform in Python

pablobaz
25pts0
www.man.com 5y ago

Fully automated, interactive plotting with JupyterLab Autoplot

pablobaz
2pts0
www.scientificamerican.com 6y ago

A Natural Log: Our Innate Sense of Numbers Is Logarithmic, Not Linear (2008)

pablobaz
1pts0
blog.cloudera.com 7y ago

YuniKorn: A universal resource scheduler from Cloudera

pablobaz
1pts0
mars-project.readthedocs.io 7y ago

Mars tensor, distributed tensor with NumPy-like API

pablobaz
3pts0
hacks.mozilla.org 7y ago

Iodide: An experimental Mozilla tool for data exploration on the web

pablobaz
300pts43
www.infoq.com 7y ago

How Airbnb Simplified the Kubernetes Workflow for 1000 Engineers

pablobaz
1pts0
www.ahl.com 7y ago

Capturing System Core Dumps at Man/AHL

pablobaz
1pts0
www.economist.com 7y ago

Python has brought computer programming to a vast new audience

pablobaz
2pts1
www.ahl.com 8y ago

A short review of Dataframes in JavaScript

pablobaz
4pts0
github.com 8y ago

An alternate JavaScript syntax that uses significant whitespace

pablobaz
1pts0
www.ahl.com 8y ago

Core Dumping, in Docker and beyond

pablobaz
5pts0
medium.com 8y ago

Quantifying Effort Through Heart Rate Data

pablobaz
1pts0
www.ahl.com 8y ago

Logging in large mathematical models

pablobaz
70pts15
www.ahl.com 8y ago

Testing with Pytest at AHL (Systematic Hedge Fund)

pablobaz
5pts0
www.outsideonline.com 8y ago

What Is “Running Power” Anyway?

pablobaz
1pts1
clipper.ai 8y ago

A low-latency prediction serving system for machine learning

pablobaz
1pts0
www.privateinternetaccess.com 8y ago

The KRACK Wi-Fi Vulnerability and Corporate Paywalls

pablobaz
3pts0
www.sciencedirect.com 8y ago

A time-lagged study of emotional intelligence and salary

pablobaz
2pts0
www.ahl.com 8y ago

The Curious Case of the Longevity of C

pablobaz
178pts301
www.ahl.com 8y ago

Why Python?

pablobaz
1pts0
www.theverge.com 8y ago

Wisconsin won’t break even on Foxconn plant deal for over two decades

pablobaz
2pts0

Sorry to hear about your aunt. My condolences. I think your misinterpreted my intent, I would dearly love a good diagnostic test for ME/CFS and agree research has been hugely underfunded.

I have followed closely the research for many years and there has been false promise of good diagnostic tests previously. What I'm arguing for is that we need a test that is specific for ME/CFS. E.g. it will test positive for a patient with ME/CFS regardless of they are obese or not, but more importantly it will not test positive for everyone who is obese. This is known as the sensitivity and specificity of the test.

What I've seen in the past is some previous ME/CFS tests show positive for groups with related symptoms but who don't have ME/CFS. This then becomes a worthless diagnostic tool. For example this would not have helped your aunt.

Hope this explains my thoughts!

I think I would need to see testing on a control group of housebound patients with other conditions to believe this. It's easy for ME testing to pick up markers for being housebound and limited exercise for an extended period of time.

That could work. 15 managers doing 10 1:1 meetings each isn't so hard. It can get tricky with people being on vacation etc. But very possible and normal.

In my experience with very large codebases, a common problem is devs trying to improve random things.

This is well intentioned. But in a large old codebase finding things to improve is trivial - there are thousands of them. Finding and judging which things to improve that will actually have a real positive impact is the real skill.

The terminal case of this is developers who in the midst of another task try improve one little bit but pulling on that thread leads to them attempting bigger and bigger fixes that are never completed.

Knowing what to fix and when to stop is invaluable.

What you are seeing is probably cold induced vasodilation

https://pmc.ncbi.nlm.nih.gov/articles/PMC4843861/

Incidentally there are some studies that show you get better at it with more frequent exposure. I have kayaked for many years and have found this to be the case - if my hands get cold now, dipping them into the water to further cool then hence opening the veins is very effective if counterintuitive way of warming my hands up.

As the article discusses you don't need to ban alcohol you can just make it more awkward: - tax it - restrict the sales by age, location and time(see Nordic countries for a really strict version of this) - minimum unit pricing - warning labels Etc. You can argue if this is the right thing to do or not but it is enforceable and there's good evidence that these measures reduce consumption and harms.

The difference between the rushed 10mins you get with the NHS and the considered 30mins you get private is amazing. You leave feeling like you’ve been taken care of and all your questions have been answered.

This is true for fairly simple cases. But when something is complex or very serious you want a true multidisciplinary team that sees the most cases per annum - that is the NHS.

A private consultant in a nice office with a very nice efficient secretary is great for their particular expertise but outside of that poor. This is based on more experience personally and with family than I would wish anyone to have.

A friend once explained his philosophy to me, that I find helpful: "Once you've written it, it's just code. Someone can always find a better way or improvements and that's fine"

I think the second sentence is true for everyone's code and that's what makes the job interesting.

Also jobs rarely aim for perfection, they aim to create value efficiently for the business. If the best way of getting there is producing code with a few mistakes that are when later picked up in a code review then that's fine too.

If this resonates with you at all, then when something annoys you repeating to yourself "It's just code" might help. Best of luck!

It's often more to provide backup and justification for a decision. Even if it then goes wrong you can say "Deloitte told me to do it".

While this may be true, it still doesn't take away two strengths consultants can bring: - never underestimate the value an independent view can bring, especially to a big company suffering from group think - secondly, a common consulting practice is to re-sell successful projects to other clients. Obviously not the exact IP, but the experience and general approach. This can be invaluable.

Airflow 2.0 6 years ago

I’ve used both extensively.

Here is my personal opinion of some Pros and Cons for the types of jobs that are in the fuzzy area of overlapping functionality.

Jenkins gui and interface handles lots of standalone jobs more nicely.

Jenkins has much better support for parameterised jobs that can be kicked off manually.

Airflow can handle dependencies between jobs in a much better way. Nicely defining and visualising dags of job really is the killer feature.

Browsing task/job logs is nicer in Airflow IMO.

Airflow scheduler is flaky - hopefully better in 2.0.

Airflow has much more “magic” than Jenkins this is often infuriating.

All that said, my preference is to move jobs to Airflow. Getting a nice gui for manually triggered jobs in airflow is/was the only large missing piece for me.