Data Driven Investor
medium.com/datadriveninvestor · Group blog · on HN since 2018
Data Driven Investor is a Medium publication with varied posts on programming, data analytics, PWAs, Bitcoin, and startups.
What HN saysHN links it for individual articles, such as the story of the NSA calling a developer and an explainer on time series databases.
93HN people shared it
14linked it in comments
111stories submitted
719story points
3 years agolast shared
2018people per year2026
Most-shared posts
- 1The NSA called me after midnight and requested my source code (2018)7 people · 416 points · first shared 2018 · 212 comments on HN
- 2Basics: How to stop using console.log() and start using your browser’s debugger3 people · 6 points · first shared 2018 · discussion on HN
- 3Don’t learn a programming language, solve a problem instead3 people · 6 points · first shared 2019 · discussion on HN
- 4Data Analytics Terms Every Beginner Should Know2 people · 3 points · first shared 2020 · discussion on HN
- 5Does PWA is good for enterprises?2 people · 1 points · first shared 2019 · discussion on HN
- 6Why Bitcoin Could Be Banned or Criminalized in the Coming Years1 people · 46 points · first shared 2020 · 76 comments on HN
- 7Fact: There Is Room for Your Big Software Idea1 people · 25 points · first shared 2019 · 9 comments on HN
- 8Springer Released 65 Free Machine Learning, CS, Data Science, Web Dev Books1 people · 19 points · first shared 2020 · 4 comments on HN
- 9Why Tesla Is Going to Win in Autonomy1 people · 11 points · first shared 2019 · 6 comments on HN
- 10How we built our equal-pay system1 people · 8 points · first shared 2020 · 2 comments on HN
- 11Automation Will Not Create More Jobs Than It Destroys1 people · 6 points · first shared 2019 · discussion on HN
- 12Archaeology in the Age of AI1 people · 5 points · first shared 2020 · discussion on HN
- 13SaaS Margins Are Terrible1 people · 5 points · first shared 2019 · 1 comments on HN
- 14Mathematical Notation for Python Developers (Part 1)1 people · 5 points · first shared 2020 · discussion on HN
- 15I Finished Andrew Ng’s Machine Learning Course and I Felt Great1 people · 5 points · first shared 2019 · discussion on HN
What HN people wrote when they linked it
raynchad · 2019-06-07
https://medium.com/datadriveninvestor/acorns-worth-the-hype-df4b76b0e6…
cronix · 2019-04-06
It's kind of funny that PWA was Jobs original vision for iOS apps with HTML5, before they came up with the walled garden cash cow approach.
> “The full Safari engine is inside of iPhone. And so, you can write amazing Web 2.0 and Ajax apps that look exactly and behave exactly like apps on the iPhone. And these apps can integrate perfectly with iPhone services. And guess what? There’s no SDK that you need! You’ve got everything you need if you know how to write apps using the most modern web standards to write amazing apps for the iPhone today. So developers, we think we’ve got a very sweet story for you. You can begin building your iPhone apps today.” - Steve Jobs/iPhone announcement Jan 2007 at macworld
https://medium.com/datadriveninvestor/2019-the-year-of-progressive-web…
What's old, is new again, 12 years later. It's how it always should have been. And guess what? There's no SDK that you need!! ;)
santafen · 2020-07-28
Here's a Medium post on Time Series Databases: https://medium.com/datadriveninvestor/what-are-time-series-databases-a… But basically, they are databases where the time dimension is a critical aspect of the data. They handle never-ending streams of incoming time-stamped data. Think of streaming stock prices, or streaming temperature data from a sensor. You want to be able to query your data specifically in a time dimension -- let's see the temperature fluctuations over the past 24 hours, including the mean. Stuff like that.
A 'normal one' is typically used for things like transactional data which adds, deletes, and updates data among linked tables. While these transactions happen in time, the time component isn't necessarily a critical dimension of the data.
alsargent · 2020-05-01
Interesting story about how this developer got called by the NSA, who instructed him to hang up then call back the publicly listed number for the agency. Exactly the steps that big banks should take. https://medium.com/datadriveninvestor/why-the-nsa-called-me-after-midn…
abvdasker · 2019-11-30
Nobody earns a billion dollars.
People who take your view that billionaires deserve their money because they "work hard" -- and I'm sure some of them do work hard -- usually don't realize how much money a billion dollars really is. An individual could never work hard enough or long enough or smart enough to deserve that amount of money.
- A million seconds ago was 12 days ago. A billion seconds ago was the 80s.
- With a 5% return on their wealth -- most billionaires actually make closer to 10% returns -- you make $137,000 a day if you have a billion dollars. So the poorest billionaires make more money in a day than 99% of Americans make in an entire year.
- https://medium.com/datadriveninvestor/you-have-no-idea-how-much-1-bill…
Nobody should have that much money. Nobody.
justanotherhn · 2019-08-23
Perhaps OP is referring to traking based on the coding? I.E. if you had all the code repos from an individual and ran some sort of pattern reconition software to cross refrence thigs like folder structure, layout of the code, frequency and time of uploads, function & variable naming techniques, etc. This reminds me of a technique called eBiomentrics[0]
[0] https://medium.com/datadriveninvestor/keystroke-dynamics-what-is-it-be…
defertoreptar · 2019-07-27
70% of rich families lose their wealth by the second generation. http://money.com/money/3925308/rich-families-lose-wealth/
90% is lost after that. https://medium.com/datadriveninvestor/why-wealth-barely-lasts-for-3-ge…
HackingWizard · 2019-07-19
thomasjudge · 2019-07-19
bilater · 2019-05-11
Nice. Another (more) simplistic effort: https://medium.com/datadriveninvestor/a-very-simple-way-to-add-analyti…
dpflan · 2019-02-19
dazhbog · 2019-02-13
The other day I noticed that if you leave the tab open long enough the images become grainy..
I wonder if they also overlay another image that to humans looks like noise, but its a neural network attack[1][2]
[1] https://youtu.be/SA4YEAWVpbk?t=34
[2] https://medium.com/datadriveninvestor/8b966793dfe1
socaller · 2018-12-21
mistermann · 2019-12-20
I think most HN'ers can appreciate the idea that the way we read technical news articles is distinctly different from how non-technical people (say, your Grandma) would read them. Two different parties can read the exact same article, but come away with very different interpretations. (Some of the reasons for this are obvious, but depending on the topic there are also others that are not so obvious.)
In the spirit of cultivating understanding of the differences between individual people with the goal of working towards a more harmonious, peaceful future, and also just for a little tongue-in-cheek fun on a Friday morning, here is a bit of insight into how (eye-catching key phrases excerpted) a distrustful-of-all-authority, possibly insane, unapologetic conspiracy theorist hyper-critically reads articles like this...
> Transparency is at the heart of everything we do at Twitter.
"transparency", "everything"
> That’s why we routinely disclose datasets of information operations we can reliably link to state actors.
"That’s why", "reliably", "link to"
> Today, we are sharing comprehensive data about 5,929 accounts which we have removed for violating our platform manipulation policies.
"Comprehensive"
> Rigorous investigations by our Site Integrity team have allowed us to attribute these accounts to a significant state-backed information operation on Twitter originating in Saudi Arabia.
I wonder what the terms "investigations", "attribute", and "originating in Saudi…