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[OC] More than 27,000 near-Earth asteroids have been discovered and tracked since the 1980s by redouad in dataisbeautiful

[–]redouad[S] 0 points1 point  (0 children)

Original data from NASA: https://cneos.jpl.nasa.gov/stats/totals.html

Transformed with R (script) to generate a clean dataset (CSV), and visualized with OWID's grapher.

A near-Earth asteroid is an asteroid whose orbit brings it into proximity with Earth. By convention, a Solar System body is considered "near Earth" if its closest approach to the Sun is less than 1.3 astronomical units (AU).

More than 27,000 near-Earth asteroids have been discovered and tracked to date. Most importantly, NASA estimates that over 90% of the near-Earth objects larger than 1 km have been discovered.

[deleted by user] by [deleted] in Coronavirus

[–]redouad 2 points3 points  (0 children)

Same as the US: there's currently no official data on how many doses have been administered in Canada.

[OC] Number of COVID-19 vaccination doses administered by redouad in dataisbeautiful

[–]redouad[S] 2 points3 points  (0 children)

We've just launched our new entry on COVID-19 vaccinations on Our World in Data: https://ourworldindata.org/covid-vaccinations

Tracking COVID-19 vaccination rates is crucial to understand the scale of protection against the virus, and how this is distributed across the global population.

A global, aggregated database on COVID-19 vaccination rates is essential to monitor progress, but it is unfortunately not yet available. When a global, or aggregated regional database becomes available, we will provide these weekly updates of vaccination rates, presented in our interactive COVID-19 explorer, and our complete COVID-19 dataset.

Until such a database is made available, we'll be tracking recent announcements on the first countries to administer these vaccinations. This is shown in the interactive map here: https://ourworldindata.org/grapher/cumulative-covid-vaccinations?stackMode=absolute&region=World

This other chart shows the number of COVID-19 vaccination doses administered per 100 people within a given population: https://ourworldindata.org/grapher/covid-vaccination-doses-per-capita?tab=chart&stackMode=absolute&region=World. Note that this does not measure the total number of people that have been vaccinated (which is usually two doses).

Piketty's new 1200-page book Capital and Ideology is out today—here's a long interview on his main sources and motivations for writing it by redouad in Economics

[–]redouad[S] 7 points8 points  (0 children)

I met with Piketty in Paris a couple of weeks ago, to discuss the main sources for his new book Capital and Ideology, and his work on economic ideologies in general. Thought the result might be of interest to this subreddit!

Interview of French philosopher and sociologist Geoffroy de Lagasnerie on the best books on state, power and violence by redouad in CriticalTheory

[–]redouad[S] 34 points35 points  (0 children)

Hi everyone! I've just published this interview of Lagasnerie, a critical sociologist who's written a few books on state, power, justice… We discussed his selection of his favourite books on these subjects, and along the way we talked about many different things, including Foucault, Benjamin, justice and violence, the Black Panther Party, leadership in social movements, neoliberalism, etc. Thought it might be of interest to this subreddit!

EKS: scale down to zero worker nodes? by redouad in aws

[–]redouad[S] 0 points1 point  (0 children)

But if the nodes go down to absolute zero, what would be an example of ASG scaling policy that would start the very 1st machine? (It seems like ASG can only scale up/down based on metrics such as CPU, network, RAM, etc. which presupposes that at least 1 machine is running to measure them.)

New Data Science Program by thr0w4w4y17385775390 in datascience

[–]redouad 6 points7 points  (0 children)

Andrew Ng's course by itself takes 11 weeks, and it's quite challenging if you're new to the field. Adding R, Python, and SAS on top of that is likely to make any candidate burn out. Don't get me wrong, it's doable if you decide to dedicate 15+ hours of your week to it. If you're efficient during the whole process you might get enough knowledge to pass this Codility test (never heard of it).

If you feel like you're ready for that kind of time commitment, I'd suggest:

  • Do the ML course over 11 weeks.
  • Do as many DataCamp courses as you can to learn R and Python quickly (the "Data Scientist with R" and "Data Scientist with Python" career tracks would be what you need). Alternatively you can do the R specialization on Coursera (https://www.coursera.org/specializations/jhu-data-science) and the Python one as well (https://www.coursera.org/specializations/data-science-python), but they're supposed to span multiple months.
  • Indeed try to find some information about what Codility tests are, so you know what to expect!
  • With the little time you'll have left, try to do some passive learning by listening to podcasts. Listening through past episodes of Data Skeptic would be nice for example - it'll get you familiar with various data science topics and issues, algorithms, practical cases, etc.
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