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Let's try to not put people down for self learning. Knowledge can be found anywhere. Those that mock people like this will soon find themselves left behind wi

by wolco 7y ago

Let's try to not put people down for self learning. Knowledge can be found anywhere. Those that mock people like this will soon find themselves left behind with ancient university based education. Unless you plan to re-enroll every 10 years the world will pass you by if you are not self learning.

throwawayjava 7y ago
"Oh boy, I can hear the sophomore software engineering studio students firing up their word processors from here" works just as well. I don't think the critique was of self-learning or bootcamps. It was a critique of a certain sort of cringe-worthy self-promotion. And not just cringe-worthy. Spreading information based upon a cursory analysis of some CSV files without any training or experience in epidemiology, public health, public communications, etc. seems... irresponsible. Also, off-topic, but most of my peers at university taught themselves how to program years before starting college -- typically in middle/early high school. And I mean actually taught themselves, from books and zine tutorials, not 'attended a formal course of instruction that was offered by a venture-backed firm instead of a formal course of instruction at a traditional university'. I guess times have changed, but the characterization of university students in CS as 'not self-taught programmers' is definitely the opposite of my experience. You came into the CS degree knowing how to program and learned how to do CS. And the characterization of "anything not university" as "self-taught" -- even formal courses of instruction that cost five figures -- is even more strange.
- SpicyLemonZest 7y ago
  That just doesn't seem like a fair standard. Why should only experts in a relevant field talk about the coronavirus? Nobody tries to stop people from sharing hospital stories from their friend's cousin's boyfriend who's a nurse.
  - throwawayjava 7y ago
    Oh, I think it's completely fine to play with the data and talk about it with friends. But SEOd medium posts have different reach potential than a facebook comment/phone call with friends/family. That's kind of the whole point of them.
    - SpicyLemonZest 7y ago
      I get what you're saying, but I don't consider the two things separate magisteria. I don't think there's anything generally wrong with people trying to spread honest ideas they've had, even if they aren't experts.
      - ghostpepper 7y ago
        For something like Covid, I'd question how much time should be spent on "trying to spread" vs the amount of time spent on refining the idea.
  - Uehreka 7y ago
    One thing about experts is that they’ve usually made it through the Dunning-Kruger “confidence pit” and come out the other side. They’re often cautious about making very strident remarks, and when they are really confident in a conclusion, it’s usually because it has a very high probability of being correct. When someone new to a field comes to a contrarian conclusion, they’re often willing to show more confidence in their conclusion because of the Dunning-Kruger effect. This makes it hard to take non-experts at their word, since they’re often unaware of how likely they are to be wrong. Now, if a total non-expert had come out of nowhere with an analysis that contradicted the public health establishment, definitively showed that the danger was massively overblown, and was right, that would be one thing. But this medium post was incorrect in its conclusion, quite confident in its conclusion, and advised courses of action that would put many people in danger (such as reopening schools).
    - SpicyLemonZest 7y ago
      I'm not sure which medium post you're referring to here. I'm sure people do sometimes write incorrect advice on Medium that would be dangerous if followed, but experts can do the same thing. Remember when the WHO said not to ban travel? I'm also not sure that distinguishes the case I mentioned. It might also cause problems to assume some particular anecdote is true and representative.
    - thu2111 7y ago
      That's a very romanticised view of expertise that doesn't match what is seen in the real world. If your view were true the replication crisis would not be happening, but it's barely even got started.
- rcpt 7y ago
  Self promotion is a skill. If it makes you cringe you need to get better at it.
  - hobs 7y ago
    Self promotion with ??? analysis about public health crisis should make EVERYONE cringe.
  - throwawayjava 7y ago
    Not all self promotion is good self promotion. I've nuked candidates because their online portfolios demonstrate bad technical judgement, questionable professional ethics, a fundamental misunderstanding of core ideas, etc. Put more simply: a portfolio is a demonstration of your work. Anything you put out in public with your name on it is part of your portfolio. Obviously, don't put bad work in your public portfolio. There's a reason you see very few serious data scientists publishing hot takes on their medium blogs -- it's a serious threat to your professional integrity and brand if you get it wrong. The only people I know & respect who are writing publicly about this topic have SME collaborators. (Of course, we're all playing with the data and talking about it in private with friends/coworkers over coffee.) Self promotion specifically by spreading your amateur take on a health crisis seems a bit... immoral? Or at least the sort of thing that makes me question the candidate's judgement. If you want to write publicly and in a formal way on this topic, get a subject matter expert to serve as a co-author. Anything less is more risky than it's worth, even from a purely selfish perspective.
- jwilber 7y ago
  Love your layers of hate-keeping. Not only did they learn before uni, they actually learned before uni, none of that fake bs! Never mind that most of the people learning before uni did so from opportunity - they often had an engineer in the family or lived in a well-to-do area where such skills were apparent. (This magnified even further the older you are). FWIW, I studied CS at a great cs uni (cal), and most of my peers were not self-taught. They still ended up at the same companies in the same positions as those who did ️.
  - commandlinefan 7y ago
    > I studied CS at a great cs uni Do you feel that your time there was wasted, and that you would have been better off attending a more focused bootcamp?
    - jwilber 7y ago
      Not at all. My twin brother went that route, and we’re both at FAANG. I also don’t feel any different for not having done much cs before uni.
nightski 7y ago
Agreed, it's an arrogant and condescending comment that does not belong on HN let alone at the top. It's sad.
- jsjddbbwj 7y ago
  It is a joke and social critique and if someone takes it seriously then that's their problem.
- commandlinefan 7y ago
  > arrogant and condescending Arrogant and condescending don’t mean “wrong”. Djikstra (the king of accusations of arrogance), once pointed out that his native language has no word for “egghead”: https://www.cs.utexas.edu/users/EWD/transcriptions/EWD12xx/EWD1209.html https://www.cs.utexas.edu/users/EWD/transcriptions/EWD12xx/E..., principally because his native culture has no history of dismissing the educated. OP is using (I interpret) “bootcamp data scientists” as a shorthand for people who know far less than they think they do. That seems like a fair characterization, honestly: that’s entirely the philosophy behind bootcamps in the first place. The idea behind them is that a four-year education in computer science is unnecessary for routine software development jobs, and one can be trained up to useful programming ability in a much shorter time (and less cost) than a full-blown university education takes. While it’s difficult to say how true this is, OP (I interpret) and I have both observed that bootcamp types seem to presume that a few-month intensive bootcamp experience actually does cover everything that a four-year degree does, and are often surprised (as well as defensive) when they come across something that their bootcamp didn’t prepare them for. A close analogue would be a paralegal thinking they know the law better than lawyers or nurses thinking they know medicine better than doctors - not that they don’t know a lot, but there are a few things that, while not as commonly useful, do come up in actual practice that are important when they do.
  - thedance 7y ago
    Well, the problem isn't that the bootcamp people lack a computer science education, it's that they lack any formal education. I've hired epistemologists and physicians to program computers and it turned out fine. The bootcamp process might in fact work well as training for otherwise educated people.
AndrewUnmuted 7y ago
Self learning would imply that the person is teaching themselves, not that the person is attending a coding boot camp. People that claim to be data scientists after attending a coding boot camp must be clowns. I’ve never come across such a person. All the data scientists I know are smart self taught people, not people who went to a boot camp.
- ahuth 7y ago
  It's possible that all the data scientists you know are not a representative sample. I've met smart data scientists and engineers who've gone to a bootcamp. People who are good and bad at their jobs come from a huge variety of backgrounds, and it's not helpful to look down on folks whose background is different than your own.
  - AndrewUnmuted 7y ago
    I am not looking down on folks different from myself. Also, I am not a data scientist. Regardless, what you are claiming is not possible. As I am sure you know, data science is a specialized field, one which draws upon a combination of statistics and computer science practices. You may be able to get some of the computer science practices down in a boot camp, but there's no way you're getting a boot camp to fill in the Bachelor's in statistics you need to be a good data scientist. Years of hard work and sincere dedication, however, I am sure can get you there.
  - CaptArmchair 7y ago
    The issue with is the word "scientist". In academia, science is the pursuit of postulating a falsifiable theory, then gathering facts to verify that theory, and then going through a process of intensive peer review that either confirms, dispels or amends those findings. The formality of the academic process is a necessity. The value of scientific findings entirely depends on the trustworthiness of the research. That is, how were the results obtained, which line of thinking was followed, did the research exclude crucial biases, etc.? The importance here is that academic research is used as a pillar to produce products and services we all use in daily life. For instance, if you need a hip replacement, you want to be sure that prosthetic was designed based on rigorous scientific findings and studies that can vouch for safety and comfort. The difference then with "data scientist" is that they often they don't apply the same rigorous research practices. It's easy to pick a dataset and bang off visualizations; it's a different story to actually come up with relevant questions, assert the quality of the data at hand and publish your findings towards a community of domain experts who are actually able to review your findings. One needs in-depth domain knowledge to do that. Good data scientists will understand this limitation. They often work in a specific domain in a supporting capacity: bringing technical skills and capabilities to domain experts that don't have those skills. Then there are those who purport to practice data science while grokking datasets, creating visualisations and cobbling a blogpost together at the end of the day. That's when you need to be really wary of what they publish, even if the bigger picture contains truthiness. Hence why I have extremely mixed feelings about what https://medium.com/@tomaspueyo https://medium.com/@tomaspueyo is doing. To be sure, the core points of what he's telling are in line with what domain experts are telling us. But the extreme number juggling is quite mind bending. Moreover, the man is not a domain expert. He's an entrepreneur who happens to know how to write viral blogposts such as "how to deliver your funny speech" and "How to become the best in the world at something". What he does is anything but scientific. And so, even though he's making a heartfelt plea heard by many, one should be careful to not take the precise details in his pieces at face value. At the moment, we all are victims of our own confirmation bias. Each day yields another data point, and given our desperate state, we want to see trends that confirm improvement, a probability that one will survive this, low mortality and so on. The reality is that we only have so few datapoints and it's still far too soon to make conclusive assertions about how this will pan out for the world at large and you in particular.
minimaxir 7y ago
As someone who learnt data science almost entirely by self-learning (and getting eviscerated by HN whenever my work hit the front page), public datasets were an immensely important tool for prototyping and refining my data analysis skills. However... The coronavirus is a case where it's very easy to unintentionally misinterpret the data, and casual analysis will likely add more noise/false information which is not what is needed now. (and any analysis will become out-of-date very quickly).
- 0az 7y ago
  I agree. If there's been a recurring theme in every single data-touching class in my DS major, it's been ethics.
  - kohtatsu 7y ago
    I'm happy to hear that. Ethics is oft-neglected, but I believe it's imperative that we guide our efforts using it.
  - bathtub365 7y ago
    Now, if we could only get SE and DS professionals to stop working on mass surveillance and population manipulation systems.
- deleted 7y ago
  [deleted]
slg 7y ago
I don't think people care about the source of learning. We care about the people who fall into the Dunning-Kruger effect and think their self learning puts them above people who dedicated a large portion of their lives to learning the same subject. An important part of self learning is being aware of your own level of knowledge. So feel free to play around with this dataset. Feel free to post to Medium what you find as long as you are clear it is a learning exercise. You don't want to actively mislead or be used as a prop for others to mislead especially during this time of crisis.
- arvinsim 7y ago
  > Feel free to post to Medium what you find as long as you are clear it is a learning exercise. You don't want to actively mislead or be used as a prop for others to mislead especially during this time of crisis. Some people can profit from this. Hence, the incentive.
digikata 7y ago
The irony might be the massive human scale effort the NYT is putting in to gather and vet the data. The most interesting self learning side effort for this, might not be analyzing the data, but trying to automate the data collection from public sites checked against the nyt data.
tropdrop 7y ago
While I agree that mocking people for self-learning is atrocious, I don't understand why in the same breath, you felt compelled to mock a university based education. Some people thrive in the bootcamp scene, while others enjoy the structure of a university. Both can be great tools for self-learning (I am thinking specifically of the resources a large university can provide, like media and electronics labs for creative projects that involve expensive cameras, 3D printers, etc), and both can be misused. University based education does not have to be ancient.
scottLobster 7y ago
He's not putting down people for self-learning, he's putting down people who think that they're an authority on a subject because they put in a few 70 hour weeks in a classroom.
- nstart 7y ago
  I understand that sentiment. But at the same time, if it ain't misinformation, I'm not sure what's wrong here. Sometimes the way to get started is by writing stuff while you are still too arrogant to not doubt (said with much affection). From code to essays, people's pasts are littered with stuff they cringe at years later. But it is what gets them started. So yea. Maybe we don't put anyone on a pedestal for shiny charts. But maybe we don't tear them down either :) (also I say this fully appreciating that you were explaining the parent poster's view and you may not necessarily support it)
  - entee 7y ago
    The issue is that making a mistake here isn't like making a mistake about, say, movie review sentiment analysis. Already there have been a few "I know stats!" posts that didn't do the right controls but still got sent around the internet as proof of someone's argument (see the "Viral advertising exec now knows epidemiology" post that medium took down). These data are confusing and difficult. It turns out there's a bunch of people who have studied this field for years and can help us avoid those issues (epidemiologists). We should listen to them. That's not to say we shouldn't open the data, but handle with extreme care, which isn't the modality of most early data scientists. A 4 week bootcamp doesn't lead to the most rigorous science, usually that's not a big issue (Pareto principle and all that), but when it's lives and active problems, it can become a big issue. I say this as a graduate of Insight which is a kind of DS bootcamp.
    - thu2111 7y ago
      No! We should rigorously scrutinise epidemiologists and do lots and lots of competing analysis. What makes you think epidemiologists are so great? The one who has guided the UK's response has been severely criticised by fellow academics in the past for bogus low quality modelling. The Imperial College paper has basic errors and flawed assumptions that are obvious even to untrained laymen. I think you're wildly over-estimating how much statistical and logical training most academics get. This is one of the basic underlying problems that the replication crisis has exposed: an unending flood of academic papers, especially those doing modelling, that fall apart when examined by people with statistical and mathematical training. You're right that a 4 week bootcamp won't make someone a flawless handling of data. But it might still be a more rigorous form of training than epidemiologists get.
jhayward 7y ago
Lets also not give machine guns to monkeys and let them loose in crowds. There is a time and place for naive, exploratory, or just plain wrong-headed exposition. Making plausible looking but wrong "scientific" prognostications in the middle of a global emergency isn't one of them.

by wolco 7y ago

throwawayjava 7y ago

"Oh boy, I can hear the sophomore software engineering studio students firing up their word processors from here" works just as well. I don't think the critique was of self-learning or bootcamps. It was a critique of a certain sort of cringe-worthy self-promotion. And not just cringe-worthy. Spreading information based upon a cursory analysis of some CSV files without any training or experience in epidemiology, public health, public communications, etc. seems... irresponsible. Also, off-topic, but most of my peers at university taught themselves how to program years before starting college -- typically in middle/early high school. And I mean actually taught themselves, from books and zine tutorials, not 'attended a formal course of instruction that was offered by a venture-backed firm instead of a formal course of instruction at a traditional university'. I guess times have changed, but the characterization of university students in CS as 'not self-taught programmers' is definitely the opposite of my experience. You came into the CS degree knowing how to program and learned how to do CS. And the characterization of "anything not university" as "self-taught" -- even formal courses of instruction that cost five figures -- is even more strange.

SpicyLemonZest 7y ago
That just doesn't seem like a fair standard. Why should only experts in a relevant field talk about the coronavirus? Nobody tries to stop people from sharing hospital stories from their friend's cousin's boyfriend who's a nurse.
- throwawayjava 7y ago
  Oh, I think it's completely fine to play with the data and talk about it with friends. But SEOd medium posts have different reach potential than a facebook comment/phone call with friends/family. That's kind of the whole point of them.
  - SpicyLemonZest 7y ago
    I get what you're saying, but I don't consider the two things separate magisteria. I don't think there's anything generally wrong with people trying to spread honest ideas they've had, even if they aren't experts.
    - ghostpepper 7y ago
      For something like Covid, I'd question how much time should be spent on "trying to spread" vs the amount of time spent on refining the idea.
- Uehreka 7y ago
  One thing about experts is that they’ve usually made it through the Dunning-Kruger “confidence pit” and come out the other side. They’re often cautious about making very strident remarks, and when they are really confident in a conclusion, it’s usually because it has a very high probability of being correct. When someone new to a field comes to a contrarian conclusion, they’re often willing to show more confidence in their conclusion because of the Dunning-Kruger effect. This makes it hard to take non-experts at their word, since they’re often unaware of how likely they are to be wrong. Now, if a total non-expert had come out of nowhere with an analysis that contradicted the public health establishment, definitively showed that the danger was massively overblown, and was right, that would be one thing. But this medium post was incorrect in its conclusion, quite confident in its conclusion, and advised courses of action that would put many people in danger (such as reopening schools).
  - SpicyLemonZest 7y ago
    I'm not sure which medium post you're referring to here. I'm sure people do sometimes write incorrect advice on Medium that would be dangerous if followed, but experts can do the same thing. Remember when the WHO said not to ban travel? I'm also not sure that distinguishes the case I mentioned. It might also cause problems to assume some particular anecdote is true and representative.
  - thu2111 7y ago
    That's a very romanticised view of expertise that doesn't match what is seen in the real world. If your view were true the replication crisis would not be happening, but it's barely even got started.
rcpt 7y ago
Self promotion is a skill. If it makes you cringe you need to get better at it.
- hobs 7y ago
  Self promotion with ??? analysis about public health crisis should make EVERYONE cringe.
- throwawayjava 7y ago
  Not all self promotion is good self promotion. I've nuked candidates because their online portfolios demonstrate bad technical judgement, questionable professional ethics, a fundamental misunderstanding of core ideas, etc. Put more simply: a portfolio is a demonstration of your work. Anything you put out in public with your name on it is part of your portfolio. Obviously, don't put bad work in your public portfolio. There's a reason you see very few serious data scientists publishing hot takes on their medium blogs -- it's a serious threat to your professional integrity and brand if you get it wrong. The only people I know & respect who are writing publicly about this topic have SME collaborators. (Of course, we're all playing with the data and talking about it in private with friends/coworkers over coffee.) Self promotion specifically by spreading your amateur take on a health crisis seems a bit... immoral? Or at least the sort of thing that makes me question the candidate's judgement. If you want to write publicly and in a formal way on this topic, get a subject matter expert to serve as a co-author. Anything less is more risky than it's worth, even from a purely selfish perspective.
jwilber 7y ago
Love your layers of hate-keeping. Not only did they learn before uni, they actually learned before uni, none of that fake bs! Never mind that most of the people learning before uni did so from opportunity - they often had an engineer in the family or lived in a well-to-do area where such skills were apparent. (This magnified even further the older you are). FWIW, I studied CS at a great cs uni (cal), and most of my peers were not self-taught. They still ended up at the same companies in the same positions as those who did ️.
- commandlinefan 7y ago
  > I studied CS at a great cs uni Do you feel that your time there was wasted, and that you would have been better off attending a more focused bootcamp?
  - jwilber 7y ago
    Not at all. My twin brother went that route, and we’re both at FAANG. I also don’t feel any different for not having done much cs before uni.

nightski 7y ago

Agreed, it's an arrogant and condescending comment that does not belong on HN let alone at the top. It's sad.

jsjddbbwj 7y ago
It is a joke and social critique and if someone takes it seriously then that's their problem.
commandlinefan 7y ago
> arrogant and condescending Arrogant and condescending don’t mean “wrong”. Djikstra (the king of accusations of arrogance), once pointed out that his native language has no word for “egghead”: https://www.cs.utexas.edu/users/EWD/transcriptions/EWD12xx/EWD1209.html https://www.cs.utexas.edu/users/EWD/transcriptions/EWD12xx/E..., principally because his native culture has no history of dismissing the educated. OP is using (I interpret) “bootcamp data scientists” as a shorthand for people who know far less than they think they do. That seems like a fair characterization, honestly: that’s entirely the philosophy behind bootcamps in the first place. The idea behind them is that a four-year education in computer science is unnecessary for routine software development jobs, and one can be trained up to useful programming ability in a much shorter time (and less cost) than a full-blown university education takes. While it’s difficult to say how true this is, OP (I interpret) and I have both observed that bootcamp types seem to presume that a few-month intensive bootcamp experience actually does cover everything that a four-year degree does, and are often surprised (as well as defensive) when they come across something that their bootcamp didn’t prepare them for. A close analogue would be a paralegal thinking they know the law better than lawyers or nurses thinking they know medicine better than doctors - not that they don’t know a lot, but there are a few things that, while not as commonly useful, do come up in actual practice that are important when they do.
- thedance 7y ago
  Well, the problem isn't that the bootcamp people lack a computer science education, it's that they lack any formal education. I've hired epistemologists and physicians to program computers and it turned out fine. The bootcamp process might in fact work well as training for otherwise educated people.

AndrewUnmuted 7y ago

Self learning would imply that the person is teaching themselves, not that the person is attending a coding boot camp. People that claim to be data scientists after attending a coding boot camp must be clowns. I’ve never come across such a person. All the data scientists I know are smart self taught people, not people who went to a boot camp.

ahuth 7y ago
It's possible that all the data scientists you know are not a representative sample. I've met smart data scientists and engineers who've gone to a bootcamp. People who are good and bad at their jobs come from a huge variety of backgrounds, and it's not helpful to look down on folks whose background is different than your own.
- AndrewUnmuted 7y ago
  I am not looking down on folks different from myself. Also, I am not a data scientist. Regardless, what you are claiming is not possible. As I am sure you know, data science is a specialized field, one which draws upon a combination of statistics and computer science practices. You may be able to get some of the computer science practices down in a boot camp, but there's no way you're getting a boot camp to fill in the Bachelor's in statistics you need to be a good data scientist. Years of hard work and sincere dedication, however, I am sure can get you there.
- CaptArmchair 7y ago
  The issue with is the word "scientist". In academia, science is the pursuit of postulating a falsifiable theory, then gathering facts to verify that theory, and then going through a process of intensive peer review that either confirms, dispels or amends those findings. The formality of the academic process is a necessity. The value of scientific findings entirely depends on the trustworthiness of the research. That is, how were the results obtained, which line of thinking was followed, did the research exclude crucial biases, etc.? The importance here is that academic research is used as a pillar to produce products and services we all use in daily life. For instance, if you need a hip replacement, you want to be sure that prosthetic was designed based on rigorous scientific findings and studies that can vouch for safety and comfort. The difference then with "data scientist" is that they often they don't apply the same rigorous research practices. It's easy to pick a dataset and bang off visualizations; it's a different story to actually come up with relevant questions, assert the quality of the data at hand and publish your findings towards a community of domain experts who are actually able to review your findings. One needs in-depth domain knowledge to do that. Good data scientists will understand this limitation. They often work in a specific domain in a supporting capacity: bringing technical skills and capabilities to domain experts that don't have those skills. Then there are those who purport to practice data science while grokking datasets, creating visualisations and cobbling a blogpost together at the end of the day. That's when you need to be really wary of what they publish, even if the bigger picture contains truthiness. Hence why I have extremely mixed feelings about what https://medium.com/@tomaspueyo https://medium.com/@tomaspueyo is doing. To be sure, the core points of what he's telling are in line with what domain experts are telling us. But the extreme number juggling is quite mind bending. Moreover, the man is not a domain expert. He's an entrepreneur who happens to know how to write viral blogposts such as "how to deliver your funny speech" and "How to become the best in the world at something". What he does is anything but scientific. And so, even though he's making a heartfelt plea heard by many, one should be careful to not take the precise details in his pieces at face value. At the moment, we all are victims of our own confirmation bias. Each day yields another data point, and given our desperate state, we want to see trends that confirm improvement, a probability that one will survive this, low mortality and so on. The reality is that we only have so few datapoints and it's still far too soon to make conclusive assertions about how this will pan out for the world at large and you in particular.

minimaxir 7y ago

As someone who learnt data science almost entirely by self-learning (and getting eviscerated by HN whenever my work hit the front page), public datasets were an immensely important tool for prototyping and refining my data analysis skills. However... The coronavirus is a case where it's very easy to unintentionally misinterpret the data, and casual analysis will likely add more noise/false information which is not what is needed now. (and any analysis will become out-of-date very quickly).

0az 7y ago
I agree. If there's been a recurring theme in every single data-touching class in my DS major, it's been ethics.
- kohtatsu 7y ago
  I'm happy to hear that. Ethics is oft-neglected, but I believe it's imperative that we guide our efforts using it.
- bathtub365 7y ago
  Now, if we could only get SE and DS professionals to stop working on mass surveillance and population manipulation systems.
deleted 7y ago
[deleted]

slg 7y ago

I don't think people care about the source of learning. We care about the people who fall into the Dunning-Kruger effect and think their self learning puts them above people who dedicated a large portion of their lives to learning the same subject. An important part of self learning is being aware of your own level of knowledge. So feel free to play around with this dataset. Feel free to post to Medium what you find as long as you are clear it is a learning exercise. You don't want to actively mislead or be used as a prop for others to mislead especially during this time of crisis.

arvinsim 7y ago
> Feel free to post to Medium what you find as long as you are clear it is a learning exercise. You don't want to actively mislead or be used as a prop for others to mislead especially during this time of crisis. Some people can profit from this. Hence, the incentive.

digikata 7y ago

The irony might be the massive human scale effort the NYT is putting in to gather and vet the data. The most interesting self learning side effort for this, might not be analyzing the data, but trying to automate the data collection from public sites checked against the nyt data.

tropdrop 7y ago

While I agree that mocking people for self-learning is atrocious, I don't understand why in the same breath, you felt compelled to mock a university based education. Some people thrive in the bootcamp scene, while others enjoy the structure of a university. Both can be great tools for self-learning (I am thinking specifically of the resources a large university can provide, like media and electronics labs for creative projects that involve expensive cameras, 3D printers, etc), and both can be misused. University based education does not have to be ancient.

scottLobster 7y ago

He's not putting down people for self-learning, he's putting down people who think that they're an authority on a subject because they put in a few 70 hour weeks in a classroom.

nstart 7y ago
I understand that sentiment. But at the same time, if it ain't misinformation, I'm not sure what's wrong here. Sometimes the way to get started is by writing stuff while you are still too arrogant to not doubt (said with much affection). From code to essays, people's pasts are littered with stuff they cringe at years later. But it is what gets them started. So yea. Maybe we don't put anyone on a pedestal for shiny charts. But maybe we don't tear them down either :) (also I say this fully appreciating that you were explaining the parent poster's view and you may not necessarily support it)
- entee 7y ago
  The issue is that making a mistake here isn't like making a mistake about, say, movie review sentiment analysis. Already there have been a few "I know stats!" posts that didn't do the right controls but still got sent around the internet as proof of someone's argument (see the "Viral advertising exec now knows epidemiology" post that medium took down). These data are confusing and difficult. It turns out there's a bunch of people who have studied this field for years and can help us avoid those issues (epidemiologists). We should listen to them. That's not to say we shouldn't open the data, but handle with extreme care, which isn't the modality of most early data scientists. A 4 week bootcamp doesn't lead to the most rigorous science, usually that's not a big issue (Pareto principle and all that), but when it's lives and active problems, it can become a big issue. I say this as a graduate of Insight which is a kind of DS bootcamp.
  - thu2111 7y ago
    No! We should rigorously scrutinise epidemiologists and do lots and lots of competing analysis. What makes you think epidemiologists are so great? The one who has guided the UK's response has been severely criticised by fellow academics in the past for bogus low quality modelling. The Imperial College paper has basic errors and flawed assumptions that are obvious even to untrained laymen. I think you're wildly over-estimating how much statistical and logical training most academics get. This is one of the basic underlying problems that the replication crisis has exposed: an unending flood of academic papers, especially those doing modelling, that fall apart when examined by people with statistical and mathematical training. You're right that a 4 week bootcamp won't make someone a flawless handling of data. But it might still be a more rigorous form of training than epidemiologists get.

jhayward 7y ago

Lets also not give machine guns to monkeys and let them loose in crowds. There is a time and place for naive, exploratory, or just plain wrong-headed exposition. Making plausible looking but wrong "scientific" prognostications in the middle of a global emergency isn't one of them.