The Data Science Handbook • Hacker News Board

Re: The Data Science Handbook

#61

Post by JoergR » Mon, May 04, 2015, 6:13 PM UTC

mayukh wrote: post #49

warsheep wrote: post #30

I'm going to sound very aggressive, but I don't understand the point of this book. They say > The material in this book is too valuable not to share. and after reading the sample I feel their definition of valuable doesn't align with mine. It's a "handbook" but the chapters are interviews that don't go in depth into anything. Here's a sample "question" > Compassion is also critical for designing beautiful and intuiti…

Agree, this seems like a collection of interviews with some famous folks who are in the field of 'data science' (can we just call it stats please). A handbook is a poor description indeed. For folks interested in learning about this topic there are tons of online courses/videos on the real stuff. The stanford islr course is a great place to start

If you think data Science is just stats, you should probably read this book.

Re: The Data Science Handbook

#62

Post by choppaface » Mon, May 04, 2015, 7:28 PM UTC

warsheep wrote: post #30

I'm going to sound very aggressive, but I don't understand the point of this book. They say > The material in this book is too valuable not to share. and after reading the sample I feel their definition of valuable doesn't align with mine. It's a "handbook" but the chapters are interviews that don't go in depth into anything. Here's a sample "question" > Compassion is also critical for designing beautiful and intuiti…

To be fair, I know some of the co-authors and I'd say they're pretty sharp at data science. However, this book highlights something they're not so sharp at: self-promotion.

I believe this book is meant to be a gag in the way the original Facebook Brogrammer store was meant to be a gag. And, similarly, the authors are going to learn the consequences of having a lot of people take the gag seriously.

Re: The Data Science Handbook

#63

Post by patrickmclaren » Mon, May 04, 2015, 7:31 PM UTC

In the past, when considering the term 'Data Science', I've assumed that this is roughly equivalent to the union of Probability Models, Statistics (with a view towards Decision Theory), CS, and Graphic/Web Design (perhaps throw in some knowledge of Heuristics and Biases too.) The number of individuals with sufficient experience in all of these fields should be significantly smaller than those in any given field alone.

I am aware the the demand for Data Scientists is higher than Statisticians at the present, at least in the US. Assuming that there is a non-trivial amount of employed Data Scientists, one is led to the conclusion that there is fairly large portion of under-skilled Data Scientists.

My question is, assuming the above hypothesis, do Data Scientists, on average, under-deliver, or are job requirements lowballed to avoid failure? First thoughts would be to compare to Quants, or Actuaries.

I have a belief that Data Scientist jobs are created due to the following process: Startup founded => Data collection => Predictive Model Exists => Data Scientist => "Visually confirm" hypothesis and send to marketing department. Obviously, the current order of this chain is not correct. A priori, mere sampling does not simultaneously guarantee regularity and high Fisher information.

Re: The Data Science Handbook

#64

Post by djervain » Tue, May 05, 2015, 10:22 AM UTC

rgejman wrote: post #4

Is there a sample chapter? It's hard to know if I want to purchase it without knowing anything about how the book is written or whether it tried to achieve its purpose.

On the 'Get the book' link, the last paragraph states: 'We have set a minimum contribution of _FREE and a suggested contribution of $19 to cover the time and investment the four of us put into this book.' The 19$ is the _suggested_ price, the actual sum is up to you. As you guessed it is a collection of interviews.

Re: The Data Science Handbook

#65

Post by fasteo » Wed, May 06, 2015, 3:07 PM UTC

>> Typically, books like this cost between $20 to $30

>> ... too valuable not to share

>> ... generosity

>> ... share

>> ... minimum contribution of FREE

>> ... suggested contribution of $19

This is too weird. Is this some kind of social experiment on price framing ?