Unboxing Data Science
joaomdmoura.com
Unboxing Data Science
1–8 of 8 posts
Re: Unboxing Data Science
#2With so many MOOC's about, the question "why should I read YOUR specific blog ?" still remains.
- Is it your CV (your portfolio to the outside world) ?
- Did you stumble/are stumbling across something that you didn't find many answers to ?
- Did you find a better path than the beaten one?
I've not found any of the above reasons, hence I've not blogged. Maybe I'm wrong.
Re: Unboxing Data Science
#3With so many MOOC's about, the question "why should I read YOUR specific blog ?" still remains. - Is it your CV (your portfolio to the outside world) ? - Did you stumble/are stumbling across something that you didn't find many answers to ? - Did you find a better path than the beaten one? I've not found any of the above reasons, hence I've not blogged. Maybe I'm wrong.
On my own blog, whenever I do a data science writeup, I make sure to do it on a topic that hasn't been done before, with explicit detail and open-sourced code.
...this has had the consequence of getting no pageviews since it removes the mystique of data science. :\
Re: Unboxing Data Science
#4With so many MOOC's about, the question "why should I read YOUR specific blog ?" still remains. - Is it your CV (your portfolio to the outside world) ? - Did you stumble/are stumbling across something that you didn't find many answers to ? - Did you find a better path than the beaten one? I've not found any of the above reasons, hence I've not blogged. Maybe I'm wrong.
The goal for this series os articles specifically is to provide yet another way for people to learn data science.
But what this series will offer when compared with other sources is my personal take on how I applied the techniques I learned in a real-world e-commerce business and how that drove innovation.
I also struggled when learning some of the lessons I'll share, because of how the information was spread, in this series of posts I'll try to put it together in a way that would have helped back them.
Re: Unboxing Data Science
#5With so many MOOC's about, the question "why should I read YOUR specific blog ?" still remains. - Is it your CV (your portfolio to the outside world) ? - Did you stumble/are stumbling across something that you didn't find many answers to ? - Did you find a better path than the beaten one? I've not found any of the above reasons, hence I've not blogged. Maybe I'm wrong.
On my own blog, whenever I do a data science writeup, I make sure to do it on a topic that hasn't been done before , with explicit detail and open-sourced code. ...this has had the consequence of getting no pageviews since it removes the mystique of data science. :\
btw the idea is to share the code and the details bu into chunks instead. I found this more helpful and less overwhelming for newcomers
Re: Unboxing Data Science
#6With so many MOOC's about, the question "why should I read YOUR specific blog ?" still remains. - Is it your CV (your portfolio to the outside world) ? - Did you stumble/are stumbling across something that you didn't find many answers to ? - Did you find a better path than the beaten one? I've not found any of the above reasons, hence I've not blogged. Maybe I'm wrong.
On my own blog, whenever I do a data science writeup, I make sure to do it on a topic that hasn't been done before , with explicit detail and open-sourced code. ...this has had the consequence of getting no pageviews since it removes the mystique of data science. :\
I just had a look at your NCAA visualisation. It was great, and just like your description, not something everyone would search for. So what?
It's super interesting, BECAUSE it's the first time I'm seeing those stats in the form of a 'heatmap'.
You're optimising for quality. And I just happen to think that's right.
Cookie cutter data intro's that walk you through installing anaconda....& and end up with some plt.plot(x,y) might gather some views. But they don't add anything to the ambient noise in the room.
They only encourage the (I'm assuming beginner) blogger to publicise their future work, as they've now experienced 'blogging'.
That's the only good outcome I see.
Perhaps I'm wrong.
Re: Unboxing Data Science
#7Earlier quoted context omitted.
On my own blog, whenever I do a data science writeup, I make sure to do it on a topic that hasn't been done before , with explicit detail and open-sourced code. ...this has had the consequence of getting no pageviews since it removes the mystique of data science. :\
I just had a look at your NCAA visualisation. It was great, and just like your description, not something everyone would search for. So what? It's super interesting, BECAUSE it's the first time I'm seeing those stats in the form of a 'heatmap'. You're optimising for quality. And I just happen to think that's right. Cookie cutter data intro's that walk you through installing anaconda....& and end up with some plt.plot…
Thanks for the compliment on that post! It's true I optimize for quality, but pageviews are good too!
Ideally I'd optimize for a weighted average between the two, but it's tricky without playing a bit dirty.
Re: Unboxing Data Science
#8Jus published the send chapter of it, now getting further into the details https://news.ycombinator.com/item?id=16867424