Found 8 comments on HN
dfsegoat · 2016-04-25 · Original thread
Any relation to the O'Reilly book of the same name? http://shop.oreilly.com/product/0636920018483.do

Otherwise, this is a bit confusing.

davmre · 2015-11-18 · Original thread
Andrew Ng's Coursera ML course is supposed to be pretty accessible. I've also heard good things about Machine Learning for Hackers (http://www.amazon.com/Machine-Learning-Hackers-Drew-Conway/d...).

Ultimately, ML is a mathematical discipline. You can ask for a gentle approach that gets you to the foot of the mountain, but "if you want to learn about nature, to appreciate nature, it is necessary to understand the language that she speaks in." If you want to be more than an amateur, there's not much substitute for getting comfortable with math at the level of, say, Kevin Murphy's book.

The good news is that the required math is fairly elementary - calculus, linear algebra, probability and statistics, all freshmen or maybe sophomore-level topics - so it shouldn't be beyond reach of a motivated developer able to set aside some time to learn. MOOCs and organizing study groups with friends/co-workers can help a lot here as well.

rankam · 2015-09-19 · Original thread
In my opinion, the "for hackers" title is in reference to multiple books that have been released with the "X for hackers" that targets people with hacking skills but do not have a formal background in X.

Machine Learning for Hackers http://www.amazon.co.uk/Machine-Learning-Hackers-Drew-Conway...

Design for Hackers http://www.amazon.co.uk/Design-Hackers-Reverse-Engineering-B...

Bayesian Methods for Hackers http://www.amazon.co.uk/Bayesian-Methods-Hackers-Probabilist...

EDIT: I'm not the author, but you can find Bayesian Methods for Hackers (free, released by the author) at the link below. I think it's a great resource for anyone wanting to explore Bayesian methods using Python.

https://github.com/CamDavidsonPilon/Probabilistic-Programmin...

rankam · 2013-06-17 · Original thread
Many companies that employ Data Scientists in NYC use R for their stats and ML work. While I personally prefer Python over R for ML related tasks, R does seem to be gaining traction in the private sector. I recommend ML for Hackers if you're interested in learning more about R - the author is very knowledgable and works as a Data Scientist for Facebook.

http://shop.oreilly.com/product/0636920018483.do

nwenzel · 2013-03-07 · Original thread
I found Machine Learning for Hackers to be good as a practical, case study based book for learning to apply and understand what is going on in several machine learning problems.

http://shop.oreilly.com/product/0636920018483.do http://www.amazon.com/Machine-Learning-for-Hackers-ebook/dp/...

It's definitely a practical approach. There's a lot of explanation but, despite coming from two PhD candidates, it certainly did not read like an academic paper.

It's also case study based, not necessarily algorithm based.

As a bonus, I used that book to teach myself R. I don't think it's meant to be an intro to R tutorial, but it worked for me.

All three are positives in my book.

nwenzel · 2013-03-07 · Original thread
I found Machine Learning for Hackers to be good as a practical, case study based book for learning to apply and understand what is going on in several machine learning problems.

http://shop.oreilly.com/product/0636920018483.do http://www.amazon.com/Machine-Learning-for-Hackers-ebook/dp/...

It's definitely a practical approach. There's a lot of explanation but, despite coming from two PhD candidates, it certainly did not read like an academic paper.

It's also case study based, not necessarily algorithm based.

As a bonus, I used that book to teach myself R. I don't think it's meant to be an intro to R tutorial, but it worked for me.

All three are positives in my book.

eloisius · 2012-05-04 · Original thread
I'm definitely grabbing Programming Collective Intelligence[1] and Machine Learning for Hackers[2]. Any recommendations based on those?

[1] http://shop.oreilly.com/product/9780596529321.do

[2] http://shop.oreilly.com/product/0636920018483.do

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