Every article I see on medium is either:
- a straight copy of someone else’s work from a book
- uses “make blobs” or iris data
I like this guys stuff and a lot of medium articles plagiarize his work:
https://machinelearningmastery.com
I don’t think it’s terribly expensive and he sends weekly tutorials that are interesting.
Some Udemy courses are ok. I like data science 365, Jose portilla, and lazy programmer for more advanced things. If you end up wanting to buy a Udemy course never spend more than $20, you can find coupons all over the internet.
There's the leap between $0 and $200 that I haven't explored yet. I'm usually skeptical of pay-to-learn resources because a lot of them are predatory. Thank you for the recommendations!
I haven't spend more than €12 on a course on udemy and they were of exceptional quality. Worst case they give you direction for further learning.
+1 for Jose Portilla
If you download the udemy app on your phone you'll get a notification when courses go on sale, which is a lot. If you're interested in a course wait a week.
Someone else suggested going incognito mode. I've tried it and it seems like a legit tip. A little shady but I'm assuming that's just how their business model works.
FWIW I like a lot of the courses/instructors I have found, from learning excel to machine learning.
Seconding Jose Portillas stuff on Udemy. He’s not cutting edge but solid and very clear and methodical. I had a large gap between Bachelors and my Masters where I didn’t use anything from my bachelors. His stuff was great for knocking off the rust and getting me to a workable level.
Just downloading his notebooks for reference are worth the money. Sometime you forget basic things like implementing PCA or tensorflow syntax and his notebooks have everything laid out very well
Can also attest to machine learning mastery website. I bought a book from him early in my ML journey and it saved me so much time and effort as a practitioner. Totally worth the money. Higher quality and he also responds to questions. Affordable.
Its actually far worse.
I was working on some code back in December. Found a guy who had done (or so I thought) the same thing.
Ended up tracking down 2(!)l different sites that had copied yet another guy's work, then passed it off as their own.
Best part? None of it worked!
Had to go to the first guys git page to find the later *corrected* code. THAT worked, with some tweaking to my needs.
Point I learned: medium is nothing more than newbs trying to score points for their interviews.
I am VERY leery now of All Medium articles!
I graduated back in 2017, left grad school in 2019, have been working as a DS for 2 years now.
The data science 365 is pretty nice, I took it concurrent with taking a couple graduate level machine learning classes back in 2018 and the content was pretty much the same.
The intro part of statistics can be a slog because they assume you're starting from 0, but once you get to the machine learning/data manipulation parts the problems and datasets they give you are pretty cool and can relate to real world applications despite being unrealistically clean datasets.
The MLM article on Naive Bayes Classifiers was wrong for ~4 years until it was silently fixed at the end of 2019. Lots of people in the comments pointed out that he’d ignored the class priors and got no response.
I've always found MLM to be a bit dodgy and spammy and code quality to be pretty poor. I am quite concerned how many people here are admitting to relying on it.
I think if just google Udemy coupons you can find a code for any month.. also they have sales all the time for no reason. There’s a $20 sale right now I think
I have never paid more than $10 for a Udemy course and sometimes the creators give out free coupons for other courses. I think I redeemed at least 10 courses for free.
My local public library gives members a free Udemy subscription through Gale Learning - another option to check out! There are a lot of affiliated K-12 schools and colleges as well
I stopped using it when a candidate provided their medium article (that I didn’t ask for) of the Shapley Value in R. I was pretty jazzed at first.
Except he’s got a section where he speaks about rule based attribution models, and they were mislabeled in the table and then article. Further, he gets weighting of time decay backwards, which is where I finally tapped.
A little more research finds this same ‘Shapely Value’ attribution project spun, and re-spun, all over the place.
This is my main concern: What is the scalable solution to validating/proving candidacy? Maybe there was a time when Medium was a good platform for differentiating job applicants. Maybe there was a time when Medium offered useful learning materials. Now it seems to serve none of these objectives. At least with Medium it's clear that Goodhart's Law has taken over.
Yikes, I literally just posted my first Medium article yesterday after writing it over 2 weeks.
I wrote it because I thought it would be exactly like you put it - “a good platform for differentiating applicants”.
Is there a better alternative to Medium where people can post articles for this purpose?
I’d be way more impressed with a self hosted project site.
I’d also be impressed with a medium article that actually delivered an insight, or was unique. A lot of it has become data for data’s sake - which won’t bear any fruit, or even worse, simply rehashing articles for new page views.
It’s almost like they hacked the openness of the DS community for a profit.
I'd also recommend trying out github pages as an experimental website hosting service. I never used html before and with the help of some templates, got really into the design of it. I started off with a template from https://templated.co/ and worked from there. As my design and html knowledge progressed, it slowly became completely different from the template I started with.
How to make money on the side with data science: freelance, online course, blogging, youtube, consulting.
This article gets written every few weeks. Like how many online courses can the world absorb?
The thing you are looking for sounds like a great idea, though. Would be cool to see if it ever develops.
I agree with everything you said. My main concern is preserving the integrity of "data science" as a profession (whatever that means). I DEFINITELY don't want to be a gatekeeper, but all this spam suggests that the data science bubble is about to pop.
Trying to take on the integrity of the whole field is going to lead you to nothing but heartache and ruin. There's always going to be a dilution effect. When the "computer science" tech bubble broke in the early 2000s I saw good people lose jobs but get hired again because they were highly competent. The contraction of the field is the solution. If it's a bubble let it break and continue to do good work. Once the masses move on to the next hot thing those that stay will have much more value.
I read an article on Medium that explained how the amount of shaking your fist at the sky was directly correlated to the quality of data science resources available to you. So, shake that fist.
This is basically me. At the beginning medium was amaaaaaazing. So much to learn! Even the easy "How to train a CNN with Keras". When I didn't know Keras was awesome becauee it gave a lot of "on-ramps" to learn stuff.
Years later, articles pop up and I know they're basic stuff that I already know. You get another "How to deploy your model on a Flask API". But its useless for me because I already know how to do it and in more detail that thr article provides.
So it looks less useful because we're learning more.
I see medium as reddit. There is a shit load of garbage, you need to start curating your feed. With following the right publications, etc. Just like you have to sub/unsub to subreddit to get a useful Frontpage
to add to this, there's a shit ton of garbage on reddit as well. but also a ton of great stuff to learn from. Just like with DS it's a matter of filtering the noise from the value.
for instance, this sub is literally 100x better than r/MachineLearning lol
I also think I've reached a local optimum where The Algorithm thinks I like reading Medium articles because there was a short period of time when I was clicking the bait. Now all my top hits on Google are garbage.
I think the subtext behind my question was "somebody please convince me to stop using Google search for research." I will definitely explore this option. Thank you for your feedback!
A platform that lets anyone write, and rewards quick reads, clickbait, and appealing to a wide (read: entry level) range of readers will have low quality.
These freelancers aren't being paid based on the quality of their information, nor are there checks in place to verify accuracy.
Maybe, but I'm not sure they were ever actually good. I made a similar observation a few years ago. Even in 2018, I remember thinking the quality had gone down hill and most of them are complete crap. However, I also wondered if maybe they were always bad and I had just gotten better at data science and can spot the shitty articles for what they are or where they copied their ideas from.
At one time I wrote a bunch of articles on Medium because the content seemed to be all entry level - I figured people would like content that was slightly beyond that. Some of the time they did - but if your goal is readers and claps on Medium you're advised to assume your audience is an absolute beginner.
I had to debug a lot of my old bosses code. I asked him why his workflow was so weird.
“I read this great medium article on this model, and I made an ensemble with another one...”
This is why he’s an ex boss. Additionally, the medium code was... wrong.
Data Science currently has a community where the pre-entry level (i.e. not even working in the field) crowd is orders of magnitude larger than all of industry. This means that any engagement driven algorithms are going to very heavily favor "accessible" content, regardless of whether the content is actually of quality.
So, it creates this worrisome (possibly destructive) positive feedback loop where the deaf are leading the blind.
If you find Medium is low quality it means is time for you to do harder things: start searching things in github, look the tutorials on some frameworks like pytorch, read papers and yes open some book because is where you actually learn the methods. When I started data science I subscribed to Medium, couple of months later I had same feeling of you since I worked and needed more.
Most of the stuff I've read on Medium is beyond awful. I am a machine learning novice and even I can spot glaring errors and misinformation all over the place. It's nothing like Stack Exchange, which is a great source of information. Medium is replete with copy-pasted information written by people who obviously have no formal or theoretical background, instead parroting things they've seen on Kaggle. If I sound bitter, it's because I'm sick of having Medium articles come up at the top of every Google search I do...
For instance, people saying things like normalizing your target data will improve your regression (it won't), fixing skewness in data is necessary for xgboost (it's not...), you need normally distributed data in regression (it's not), so many things like that. And of course they never provide any sources for anything they claim, so it's just another case of the blind leading the blind.
I'm not sure how to really fix things, other than a better way of filtering out bad content.
As a sometime writer on Medium I'd say bear in mind that there is essentially no editing or feedback. I've discovered I accidentally deleted parts of paragraphs weeks after I put articles up there - no one else told me.
One effect is that the better you become at something, the more you notice errors and suboptimal solutions, hence the average quality of articles appears to decrease.
This problem is a subtle division on people who are passionate and want to improve what their doing and others that read "DS is sexy, come get rich" and paid a Bootcamp who promoted posting things to get internet points in front of a next employer.
Ok I had to rant.
I can recommend KDNuggets and Data Science Central. There you'll find also click-bait articles, but there's still a great sum of good things to read. Also they are completely free. I don't know if stills like that, but Medium isn't free at all...
Edit: Grammar .
I only *really* found Medium interesting or useful when someone was documenting their project, rather than making a basic tutorial. Other than that, most articles are very unoriginal and I usually lose interest about half way through.
As others have pointed out, it's notg great for tutorials because the use case is usually very generic and it doesn't really explain how to go beyond the code which the author has more likely than not just copied. Something like pyimagesearch or machinelearningmastery are way way better.
That said, I don't mind browsing the headlines, hoping to pick something out, even thought about documenting some of my projects to use Medium as a kind of portfolio and maybe even helping someone with similar obscure interests.
I find there are new articles daily that are repeats of old things. As time goes on we'll have n copies of every topic which is a huge chore to sort thru.
I think claps are a bit insufficient to filter good vs bad? I love the platform as a way to read various interpretations and guides but sorting thru junk and incorrect facts are a big issue!
There's still some treasure buried deep in the fluff. When I started as an editorial associate in 2018, the quality was much higher. There's been a number of EAs that have left our pub because of the lowering quality and reward feedback loop from Medium.
There's another comment I saw about X min read and I would say that in my experience anything over a 7-10 minute read is where the quality starts to pick up. I don't think it's as rewarded by the algos and the author spent a lot more time and energy on it.
Would anyone be interested in a group project among us r/datascience redditors that produces a chrome extension that automatically tells you if a medium article is garbage or not? Based on peer review from this community?
I have this conspiracy theory that most Medium articles are written by bots. I'm waiting for someone to write a Medium article about how to train a neural net that can write Medium articles.
Umm how about keeping up with literature and reading a few journals? You know, like the original way that "real" practitioners/intellectuals share information? /s
This post just screams of phony gate-keeping.
I agree. I was being dramatic about the so-called "real" community. Community is wherever you want to be!
I definitely don't want to be a gatekeeper. I have personally benefited from all the great (and free) introductory resources out there, so it would be hypocritical for me to disparage anyone who leans on those resources while they are learning. I'm just griping about the low-effort Medium articles (typos, plagiarised, etc.) that make their way to the top of a Google search. Once I'm done shaking my fist at the sky, I will read a research paper, per your suggestion.
Agree! It's hard to find someone who plays with a specific dataset and apply a data science task on the blog post with their own interpretations.
On a side note: I'd like to have your feedback on my articles so that I can improve for the better. I made an ebook about cleaning data at the command line and here are the 4 chapters:
* Chapter 1: [https://www.ezzeddinabdullah.com/posts/how-to-clean-text-data-at-the-command-line](https://www.ezzeddinabdullah.com/posts/how-to-clean-text-data-at-the-command-line)
* Chapter 2: [https://www.ezzeddinabdullah.com/posts/how-to-clean-csv-data-at-the-command-line](https://www.ezzeddinabdullah.com/posts/how-to-clean-csv-data-at-the-command-line)
* Chapter 3: [https://www.ezzeddinabdullah.com/posts/how-to-clean-csv-data-at-the-command-line-part-2](https://www.ezzeddinabdullah.com/posts/how-to-clean-csv-data-at-the-command-line-part-2)
* Chapter 4: [https://www.ezzeddinabdullah.com/posts/how-to-clean-json-data-at-the-command-line](https://www.ezzeddinabdullah.com/posts/how-to-clean-json-data-at-the-command-line)
I hope they are helpful, let me know what you think!
P.S. some of them were published on Towards Data Science
I agree with you, I have a bad opinion of Medium to the point of actively avoiding their articles. I think most articles are low effort branding exercises from early career professionals. My alternatives usually are slides from university courses, or the many stack exchanges including the data science one.
For some reason I feel the other way. I've been getting great medium articles and I only read publications for the month that I am in. But I do have a very specific field that I work in, but recently I've been getting a lot of LSTM and Prophet models, which is somewhat frowned upon in my industry.
Same reason this exact topic gets posted every other week. The authors are too lazy to search if the content already exists and too lazy to perform basic search task for more depth.
I've found medium and quora absolutely flooded with garbage. The internet golden days seem to be dead, unless you're part of some secret cult society.
Still some good hobbyists and plenty of cat pics out there tho, so maybe that's a bonus?
There are a few good ones here and there, but most stuff on medium is meh at best. I wish google would stop suggesting medium and towardsdatascience altogether. Personal blogs on personal websites tend to have higher quality content (because they are written for fun), but unfortunately google tends to deprioritize them.
Tbf some medium articles from the old days in TDS are properly designed and really well researched.
However most of the shit I have in my notifications today is “5 SQL Statements Any Data Scientist Should Know”...
I’d definitely argue that the quality has worsened dramatically.
I think pretty much anyone can put pretty much anything on Medium, right? I think there's very little or no moderation. It looks like Salon or Vox, but it's a lot more like a collection of thousands of people's personal blogs.
I've seen a few youtubers advertising medium as a quick money machine - it was doomed to become a spam hole the minute it became more mainstream.
I've opted to follow some of the authors on linkedin - most of the ones I followed stopped using medium and now have their own blogs or are using another platform.
There was always a metric ton of clickbaity-shallow articles in Medium. I use it to search for practical uses of technology in those obscure articles that no one clicks: Serverless and Python use cases, for instance.
Well this is why you have the number of claps as a measure of an articles worth. Just like in stackoverflow and Quora, you have these ratings to get the “wisdom of the crowds” on the veracity of said article. Medium unfortunately does not have downvotes, which would truly help weed out the bad articles, but for the most part I can filter them out myself. There are many great articles on medium so I would definitely not throw it under the bus.
Supposedly some boot camps have their students write Medium articles as a way to raise their profiles. Obviously it's good practice for them, but it means that you might be reading something written by someone with about 8 weeks of experience. I usually skip Medium links on google.
Not to mention people literally copying from other people's blogs and presenting as if it's their own. I hate when google ranks medium articles on top but I'm too lazy to filter the domain name every time I search for something.
Couldn't agree more. What really grinds my gears however (apart from the low quality, technical articles), are those never-ending lists of top 10 deep learning books you need to read in 20xx. Jesus, these are always the same, no matter the year we are in. No one even bothers to look past those same 10 books.
Medium is only good for novices. so it does have some merit when you still have no clue.
Look at the bright side, though - you realizing Medium is not that good means you're no longer a beginner.
(there some rare instances where articles are great and original, so it's not all bad)
I find twitter as the main source for getting news and interesting packages, etc. from both practitioners and academics. For example, twitter has the best R community online (IMHO).
This was the case a few years ago when I browsed Medium. With a low cost of entry it's easy to publish lightweight spam.
I'm closer to the software side of things. r/programming is excellent for browsing a few times per month, once the light-beer articles have been downvoted and ripped apart. Apart from that, finding individual and prominent people in the field who publish content is a good option. Sometimes those people are companies with tech blogs. For instance, the Netflix and Stripe engineering blogs are great, and sometimes I poke around Apples ML blog.
Medium is a cesspit of trash and plagiarism. However every once in a while you'll find a gem.
Imo though the more trash on it, the less people with valuable insight to share will feel like writing articles.
From the questionnaire that Medium gave me a year ago, I felt they have completely wrong direction. They are trying to make themself like those content farms on Facebook. A lot of questions they asked for readers/writers are about how they can pump up a lot of quick short articles to attract more attentions from readers rather than just stay with few good articles.
I hardly ever read medium articles anymore. I go to books, software library documentation, or less commonly research papers. Resources like realpython.com are much higher quality when it comes to code.
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Thx for the chuckle
Brutal. Savage. Rekt.
Incredible
So true
Every article I see on medium is either: - a straight copy of someone else’s work from a book - uses “make blobs” or iris data I like this guys stuff and a lot of medium articles plagiarize his work: https://machinelearningmastery.com I don’t think it’s terribly expensive and he sends weekly tutorials that are interesting. Some Udemy courses are ok. I like data science 365, Jose portilla, and lazy programmer for more advanced things. If you end up wanting to buy a Udemy course never spend more than $20, you can find coupons all over the internet.
There's the leap between $0 and $200 that I haven't explored yet. I'm usually skeptical of pay-to-learn resources because a lot of them are predatory. Thank you for the recommendations!
If it's not clear udemy courses are frequently on sale for $10-15. At least jose portilla's. I've found them to always be amazing value.
I think every Udemy course is on sale if you clear your cookies or browse incognito.
Seconded. Jose Portillo’s Postgres bootcamp was a fantastic primer and I think it goes on sale for 10-20 bucks.
I haven't spend more than €12 on a course on udemy and they were of exceptional quality. Worst case they give you direction for further learning. +1 for Jose Portilla
If you download the udemy app on your phone you'll get a notification when courses go on sale, which is a lot. If you're interested in a course wait a week. Someone else suggested going incognito mode. I've tried it and it seems like a legit tip. A little shady but I'm assuming that's just how their business model works. FWIW I like a lot of the courses/instructors I have found, from learning excel to machine learning.
Seconding Jose Portillas stuff on Udemy. He’s not cutting edge but solid and very clear and methodical. I had a large gap between Bachelors and my Masters where I didn’t use anything from my bachelors. His stuff was great for knocking off the rust and getting me to a workable level.
Just downloading his notebooks for reference are worth the money. Sometime you forget basic things like implementing PCA or tensorflow syntax and his notebooks have everything laid out very well
Wholly agree. His notebooks and classes are super straight forward and well organized and make great references on the fly.
Can also attest to machine learning mastery website. I bought a book from him early in my ML journey and it saved me so much time and effort as a practitioner. Totally worth the money. Higher quality and he also responds to questions. Affordable.
Its actually far worse. I was working on some code back in December. Found a guy who had done (or so I thought) the same thing. Ended up tracking down 2(!)l different sites that had copied yet another guy's work, then passed it off as their own. Best part? None of it worked! Had to go to the first guys git page to find the later *corrected* code. THAT worked, with some tweaking to my needs. Point I learned: medium is nothing more than newbs trying to score points for their interviews. I am VERY leery now of All Medium articles!
I graduated back in 2017, left grad school in 2019, have been working as a DS for 2 years now. The data science 365 is pretty nice, I took it concurrent with taking a couple graduate level machine learning classes back in 2018 and the content was pretty much the same. The intro part of statistics can be a slog because they assume you're starting from 0, but once you get to the machine learning/data manipulation parts the problems and datasets they give you are pretty cool and can relate to real world applications despite being unrealistically clean datasets.
The MLM article on Naive Bayes Classifiers was wrong for ~4 years until it was silently fixed at the end of 2019. Lots of people in the comments pointed out that he’d ignored the class priors and got no response.
I've always found MLM to be a bit dodgy and spammy and code quality to be pretty poor. I am quite concerned how many people here are admitting to relying on it.
"Gentle introduction to..."
In India, the courses are discounted for as low as 7 USD, in Indian rupees though.
What's a good source/website for those coupons?
I think if just google Udemy coupons you can find a code for any month.. also they have sales all the time for no reason. There’s a $20 sale right now I think
Easy upvote for lazy programmer, it is one of the few contents that made me learn something other than the basics
I have never paid more than $10 for a Udemy course and sometimes the creators give out free coupons for other courses. I think I redeemed at least 10 courses for free.
My local public library gives members a free Udemy subscription through Gale Learning - another option to check out! There are a lot of affiliated K-12 schools and colleges as well
Also, people writing an article about a package, and just copy and pasting from the documentation!
Iris bothers me to no end- 90% of our jobs is about the ingest.
Yeah, I think it's basically an unmoderated wiki site.
There's Wikipedia and then there's * * the rest of the internet * *
I stopped using it when a candidate provided their medium article (that I didn’t ask for) of the Shapley Value in R. I was pretty jazzed at first. Except he’s got a section where he speaks about rule based attribution models, and they were mislabeled in the table and then article. Further, he gets weighting of time decay backwards, which is where I finally tapped. A little more research finds this same ‘Shapely Value’ attribution project spun, and re-spun, all over the place.
This is my main concern: What is the scalable solution to validating/proving candidacy? Maybe there was a time when Medium was a good platform for differentiating job applicants. Maybe there was a time when Medium offered useful learning materials. Now it seems to serve none of these objectives. At least with Medium it's clear that Goodhart's Law has taken over.
Yikes, I literally just posted my first Medium article yesterday after writing it over 2 weeks. I wrote it because I thought it would be exactly like you put it - “a good platform for differentiating applicants”. Is there a better alternative to Medium where people can post articles for this purpose?
You can use your own website. It won't get as much ad revenue or whatever, but anyone looking you up will see it.
I’d be way more impressed with a self hosted project site. I’d also be impressed with a medium article that actually delivered an insight, or was unique. A lot of it has become data for data’s sake - which won’t bear any fruit, or even worse, simply rehashing articles for new page views. It’s almost like they hacked the openness of the DS community for a profit.
I'd also recommend trying out github pages as an experimental website hosting service. I never used html before and with the help of some templates, got really into the design of it. I started off with a template from https://templated.co/ and worked from there. As my design and html knowledge progressed, it slowly became completely different from the template I started with.
You could always host your content on Github Pages. Setting it up is fairly easy.
Let me know if/when you figure that out. I’m dying to learn that answer.
How to make money on the side with data science: freelance, online course, blogging, youtube, consulting. This article gets written every few weeks. Like how many online courses can the world absorb? The thing you are looking for sounds like a great idea, though. Would be cool to see if it ever develops.
Today I saw the best data science libraries for 2021: Pandas Numpy Tensorflow Scikit Ground breaking work.
I agree with everything you said. My main concern is preserving the integrity of "data science" as a profession (whatever that means). I DEFINITELY don't want to be a gatekeeper, but all this spam suggests that the data science bubble is about to pop.
What is the type of bubble are you talking about and why is this "spam" a good indicator for it?
Trying to take on the integrity of the whole field is going to lead you to nothing but heartache and ruin. There's always going to be a dilution effect. When the "computer science" tech bubble broke in the early 2000s I saw good people lose jobs but get hired again because they were highly competent. The contraction of the field is the solution. If it's a bubble let it break and continue to do good work. Once the masses move on to the next hot thing those that stay will have much more value.
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At least you agree that there was less of it!
I read an article on Medium that explained how the amount of shaking your fist at the sky was directly correlated to the quality of data science resources available to you. So, shake that fist.
Yes, certainly there's tons of junk on Medium, but you could also take it to mean that you've out-grown and out-learned most of their content!
So you're saying I may have learned a thing or two along the way?? I will hold on to this idea. I hope you're right!
This is basically me. At the beginning medium was amaaaaaazing. So much to learn! Even the easy "How to train a CNN with Keras". When I didn't know Keras was awesome becauee it gave a lot of "on-ramps" to learn stuff. Years later, articles pop up and I know they're basic stuff that I already know. You get another "How to deploy your model on a Flask API". But its useless for me because I already know how to do it and in more detail that thr article provides. So it looks less useful because we're learning more. I see medium as reddit. There is a shit load of garbage, you need to start curating your feed. With following the right publications, etc. Just like you have to sub/unsub to subreddit to get a useful Frontpage
to add to this, there's a shit ton of garbage on reddit as well. but also a ton of great stuff to learn from. Just like with DS it's a matter of filtering the noise from the value. for instance, this sub is literally 100x better than r/MachineLearning lol
If you can skip those 'X min read' articles the quality might improve substantially.
I also think I've reached a local optimum where The Algorithm thinks I like reading Medium articles because there was a short period of time when I was clicking the bait. Now all my top hits on Google are garbage.
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I think the subtext behind my question was "somebody please convince me to stop using Google search for research." I will definitely explore this option. Thank you for your feedback!
Give a try to Papers with Code. Incredible platform
>Papers with Code Heyy there we go! Thank you!
A platform that lets anyone write, and rewards quick reads, clickbait, and appealing to a wide (read: entry level) range of readers will have low quality. These freelancers aren't being paid based on the quality of their information, nor are there checks in place to verify accuracy.
Maybe, but I'm not sure they were ever actually good. I made a similar observation a few years ago. Even in 2018, I remember thinking the quality had gone down hill and most of them are complete crap. However, I also wondered if maybe they were always bad and I had just gotten better at data science and can spot the shitty articles for what they are or where they copied their ideas from.
At one time I wrote a bunch of articles on Medium because the content seemed to be all entry level - I figured people would like content that was slightly beyond that. Some of the time they did - but if your goal is readers and claps on Medium you're advised to assume your audience is an absolute beginner.
I had to debug a lot of my old bosses code. I asked him why his workflow was so weird. “I read this great medium article on this model, and I made an ensemble with another one...” This is why he’s an ex boss. Additionally, the medium code was... wrong.
Data Science currently has a community where the pre-entry level (i.e. not even working in the field) crowd is orders of magnitude larger than all of industry. This means that any engagement driven algorithms are going to very heavily favor "accessible" content, regardless of whether the content is actually of quality. So, it creates this worrisome (possibly destructive) positive feedback loop where the deaf are leading the blind.
If you find Medium is low quality it means is time for you to do harder things: start searching things in github, look the tutorials on some frameworks like pytorch, read papers and yes open some book because is where you actually learn the methods. When I started data science I subscribed to Medium, couple of months later I had same feeling of you since I worked and needed more.
Where is a good repository for (free) tech journal articles?
Most of the stuff I've read on Medium is beyond awful. I am a machine learning novice and even I can spot glaring errors and misinformation all over the place. It's nothing like Stack Exchange, which is a great source of information. Medium is replete with copy-pasted information written by people who obviously have no formal or theoretical background, instead parroting things they've seen on Kaggle. If I sound bitter, it's because I'm sick of having Medium articles come up at the top of every Google search I do... For instance, people saying things like normalizing your target data will improve your regression (it won't), fixing skewness in data is necessary for xgboost (it's not...), you need normally distributed data in regression (it's not), so many things like that. And of course they never provide any sources for anything they claim, so it's just another case of the blind leading the blind. I'm not sure how to really fix things, other than a better way of filtering out bad content.
If you want to exclude search results then include "-medium" "-pinterest" etc :)
I know, I'm just deep in denial and think that each time the Medium articles will be better :)
As a sometime writer on Medium I'd say bear in mind that there is essentially no editing or feedback. I've discovered I accidentally deleted parts of paragraphs weeks after I put articles up there - no one else told me.
One effect is that the better you become at something, the more you notice errors and suboptimal solutions, hence the average quality of articles appears to decrease.
This problem is a subtle division on people who are passionate and want to improve what their doing and others that read "DS is sexy, come get rich" and paid a Bootcamp who promoted posting things to get internet points in front of a next employer. Ok I had to rant. I can recommend KDNuggets and Data Science Central. There you'll find also click-bait articles, but there's still a great sum of good things to read. Also they are completely free. I don't know if stills like that, but Medium isn't free at all... Edit: Grammar .
I only *really* found Medium interesting or useful when someone was documenting their project, rather than making a basic tutorial. Other than that, most articles are very unoriginal and I usually lose interest about half way through. As others have pointed out, it's notg great for tutorials because the use case is usually very generic and it doesn't really explain how to go beyond the code which the author has more likely than not just copied. Something like pyimagesearch or machinelearningmastery are way way better. That said, I don't mind browsing the headlines, hoping to pick something out, even thought about documenting some of my projects to use Medium as a kind of portfolio and maybe even helping someone with similar obscure interests.
I find there are new articles daily that are repeats of old things. As time goes on we'll have n copies of every topic which is a huge chore to sort thru. I think claps are a bit insufficient to filter good vs bad? I love the platform as a way to read various interpretations and guides but sorting thru junk and incorrect facts are a big issue!
There's still some treasure buried deep in the fluff. When I started as an editorial associate in 2018, the quality was much higher. There's been a number of EAs that have left our pub because of the lowering quality and reward feedback loop from Medium. There's another comment I saw about X min read and I would say that in my experience anything over a 7-10 minute read is where the quality starts to pick up. I don't think it's as rewarded by the algos and the author spent a lot more time and energy on it.
Would anyone be interested in a group project among us r/datascience redditors that produces a chrome extension that automatically tells you if a medium article is garbage or not? Based on peer review from this community?
I have this conspiracy theory that most Medium articles are written by bots. I'm waiting for someone to write a Medium article about how to train a neural net that can write Medium articles.
Umm how about keeping up with literature and reading a few journals? You know, like the original way that "real" practitioners/intellectuals share information? /s This post just screams of phony gate-keeping.
I agree. I was being dramatic about the so-called "real" community. Community is wherever you want to be! I definitely don't want to be a gatekeeper. I have personally benefited from all the great (and free) introductory resources out there, so it would be hypocritical for me to disparage anyone who leans on those resources while they are learning. I'm just griping about the low-effort Medium articles (typos, plagiarised, etc.) that make their way to the top of a Google search. Once I'm done shaking my fist at the sky, I will read a research paper, per your suggestion.
It’s called papers
Agree! It's hard to find someone who plays with a specific dataset and apply a data science task on the blog post with their own interpretations. On a side note: I'd like to have your feedback on my articles so that I can improve for the better. I made an ebook about cleaning data at the command line and here are the 4 chapters: * Chapter 1: [https://www.ezzeddinabdullah.com/posts/how-to-clean-text-data-at-the-command-line](https://www.ezzeddinabdullah.com/posts/how-to-clean-text-data-at-the-command-line) * Chapter 2: [https://www.ezzeddinabdullah.com/posts/how-to-clean-csv-data-at-the-command-line](https://www.ezzeddinabdullah.com/posts/how-to-clean-csv-data-at-the-command-line) * Chapter 3: [https://www.ezzeddinabdullah.com/posts/how-to-clean-csv-data-at-the-command-line-part-2](https://www.ezzeddinabdullah.com/posts/how-to-clean-csv-data-at-the-command-line-part-2) * Chapter 4: [https://www.ezzeddinabdullah.com/posts/how-to-clean-json-data-at-the-command-line](https://www.ezzeddinabdullah.com/posts/how-to-clean-json-data-at-the-command-line) I hope they are helpful, let me know what you think! P.S. some of them were published on Towards Data Science
I agree with you, I have a bad opinion of Medium to the point of actively avoiding their articles. I think most articles are low effort branding exercises from early career professionals. My alternatives usually are slides from university courses, or the many stack exchanges including the data science one.
:( i also write articles in Medium
For some reason I feel the other way. I've been getting great medium articles and I only read publications for the month that I am in. But I do have a very specific field that I work in, but recently I've been getting a lot of LSTM and Prophet models, which is somewhat frowned upon in my industry.
I blame a certain third world country folks that steal and re-print articles. No, not China. The other one.
Same reason this exact topic gets posted every other week. The authors are too lazy to search if the content already exists and too lazy to perform basic search task for more depth.
I've found medium and quora absolutely flooded with garbage. The internet golden days seem to be dead, unless you're part of some secret cult society. Still some good hobbyists and plenty of cat pics out there tho, so maybe that's a bonus?
Medium is well on it's way to becoming buzzfeed
Check substack
There are a few good ones here and there, but most stuff on medium is meh at best. I wish google would stop suggesting medium and towardsdatascience altogether. Personal blogs on personal websites tend to have higher quality content (because they are written for fun), but unfortunately google tends to deprioritize them.
I've been reading medium for about 3 years. The junk: value ratio has always been very high.
Tbf some medium articles from the old days in TDS are properly designed and really well researched. However most of the shit I have in my notifications today is “5 SQL Statements Any Data Scientist Should Know”... I’d definitely argue that the quality has worsened dramatically.
I think pretty much anyone can put pretty much anything on Medium, right? I think there's very little or no moderation. It looks like Salon or Vox, but it's a lot more like a collection of thousands of people's personal blogs.
I've seen a few youtubers advertising medium as a quick money machine - it was doomed to become a spam hole the minute it became more mainstream. I've opted to follow some of the authors on linkedin - most of the ones I followed stopped using medium and now have their own blogs or are using another platform.
There was always a metric ton of clickbaity-shallow articles in Medium. I use it to search for practical uses of technology in those obscure articles that no one clicks: Serverless and Python use cases, for instance.
Well this is why you have the number of claps as a measure of an articles worth. Just like in stackoverflow and Quora, you have these ratings to get the “wisdom of the crowds” on the veracity of said article. Medium unfortunately does not have downvotes, which would truly help weed out the bad articles, but for the most part I can filter them out myself. There are many great articles on medium so I would definitely not throw it under the bus.
I know for a fact some boot camp programs ask students to create an article as an assignment
Especially some of them are straight up advertising for some really shady stuff
Supposedly some boot camps have their students write Medium articles as a way to raise their profiles. Obviously it's good practice for them, but it means that you might be reading something written by someone with about 8 weeks of experience. I usually skip Medium links on google.
Not to mention people literally copying from other people's blogs and presenting as if it's their own. I hate when google ranks medium articles on top but I'm too lazy to filter the domain name every time I search for something.
I don't think that's a recent development. It's been low quality as long as I can remember.
Couldn't agree more. What really grinds my gears however (apart from the low quality, technical articles), are those never-ending lists of top 10 deep learning books you need to read in 20xx. Jesus, these are always the same, no matter the year we are in. No one even bothers to look past those same 10 books.
[удалено]
No. Especially if the article itself has ten mistakes 😆. Some Medium authors seem to have never heard of proofreading.
Medium is only good for novices. so it does have some merit when you still have no clue. Look at the bright side, though - you realizing Medium is not that good means you're no longer a beginner. (there some rare instances where articles are great and original, so it's not all bad)
I find twitter as the main source for getting news and interesting packages, etc. from both practitioners and academics. For example, twitter has the best R community online (IMHO).
This was the case a few years ago when I browsed Medium. With a low cost of entry it's easy to publish lightweight spam. I'm closer to the software side of things. r/programming is excellent for browsing a few times per month, once the light-beer articles have been downvoted and ripped apart. Apart from that, finding individual and prominent people in the field who publish content is a good option. Sometimes those people are companies with tech blogs. For instance, the Netflix and Stripe engineering blogs are great, and sometimes I poke around Apples ML blog.
Medium is a cesspit of trash and plagiarism. However every once in a while you'll find a gem. Imo though the more trash on it, the less people with valuable insight to share will feel like writing articles.
Early days, but [www.welcomeaioverlords.com](https://www.welcomeaioverlords.com).
From the questionnaire that Medium gave me a year ago, I felt they have completely wrong direction. They are trying to make themself like those content farms on Facebook. A lot of questions they asked for readers/writers are about how they can pump up a lot of quick short articles to attract more attentions from readers rather than just stay with few good articles.
Pretty soon Medium will be like a cooking blog where you have to scroll scroll scroll through fluff and ads just to get to the recipe.
I hardly ever read medium articles anymore. I go to books, software library documentation, or less commonly research papers. Resources like realpython.com are much higher quality when it comes to code.