From a personal point of view as someone also interested in learning a bit I think building something is often a good way to go. I kind of have a plan one day to hack together the neural network from http://karpathy.github.io/2015/05/21/rnn-effectiveness/ with some personally selected stock market data to see if it can kick out profitable buy/sells. (There is some how to stuff in the article under 'Source Code')
A "good" AI stock trader would in particular require some kind of real-world pseudo real-time data feed (pick your poison; Twitter, FB, news, even generic web crawling) Anything based purely on the stock charts themselves becomes simply a sophisticated pattern matcher and can't possibly respond to the actual drivers of price movement.
Ask HN: AI is going to be big. How should we learn?
11–20 of 24 posts
Re: Ask HN: AI is going to be big. How should we learn?
#12Re: Ask HN: AI is going to be big. How should we learn?
#13In addition, if you don't already have a background in Calculus and Linear Algebra, then supplement the Ng course with the Khan Academy stuff on Calculus and Linear Algebra, or other courses you can pick up on Coursera or Edx or whatever.
If you get really interested in neural networks (which are all the rage these days) after the Ng class, there's a freely available book on Neural Network design that you could look at. It doesn't cover all the very latest techniques, but it would help you build the foundation of understanding.
http://hagan.okstate.edu/nnd.html
There's also a MOOC around the Learning From Data book that you could check out.
https://work.caltech.edu/telecourse.html
OTOH, if you're making a sharp distinction between "Classic AI" and "Machine Learning" and you really care mainly about the classical stuff, then you might want to start with the Berkeley CS188 class. You can take it through EdX (https://www.edx.org/course/artificial-intelligence-uc-berkel...) or just watch the videos and download the notes and stuff from http://ai.berkeley.edu/home.html
And if you just want to dive into reading some classic papers and stuff, check out:
http://publications.csail.mit.edu/ai/pubs_browse.shtml
and/or
http://ijcai.org/past_proceedings
Another good resource is
Re: Ask HN: AI is going to be big. How should we learn?
#14You'll get a framework/app/api that will deliver you the info programmed by someone really into AI.
It'll be business as usual.
Know API's, frameworks, how to analyse data and tools around this, know people.
AKA Just be a good programmer.
Re: Ask HN: AI is going to be big. How should we learn?
#15Well, first, I would try to understand what "AI" you are talking about and why you have so much confidence it will be big. It's a pretty broad category, and a lot of it is (still) very far from commercialization. It's almost like asking about "the Internet" in 1992. Here are some categories that may help to dive into... -Computer Vision -Natural Language Processing AClustering vs classification in machine learning -N…
Re: Ask HN: AI is going to be big. How should we learn?
#16Knowing AI will be useless, it'll be like knowing and programming assembly language, for high end specialists only. You'll get a framework/app/api that will deliver you the info programmed by someone really into AI. It'll be business as usual. Know API's, frameworks, how to analyse data and tools around this, know people. AKA Just be a good programmer.
Seriously, does for you being a good programmer only consist in calling some API or knowing some framework?
Re: Ask HN: AI is going to be big. How should we learn?
#17Earlier quoted context omitted.
A "good" AI stock trader would in particular require some kind of real-world pseudo real-time data feed (pick your poison; Twitter, FB, news, even generic web crawling) Anything based purely on the stock charts themselves becomes simply a sophisticated pattern matcher and can't possibly respond to the actual drivers of price movement.
It depends on what strategy you are trying to implement. I wasn't particularly thinking real time. I'm more of a value investor at heart and was thinking of something like it looking for stocks where the valuation is underpinned by assets and buying when they are near the bottom. So the inputs would be something like some numbers from the income and balance statements plus the price graph.
... is still using some data external to the stock charts, which should work great. :)
Re: Ask HN: AI is going to be big. How should we learn?
#18Re: Ask HN: AI is going to be big. How should we learn?
#19Knowing AI will be useless, it'll be like knowing and programming assembly language, for high end specialists only. You'll get a framework/app/api that will deliver you the info programmed by someone really into AI. It'll be business as usual. Know API's, frameworks, how to analyse data and tools around this, know people. AKA Just be a good programmer.
Re: Ask HN: AI is going to be big. How should we learn?
#20Knowing AI will be useless, it'll be like knowing and programming assembly language, for high end specialists only. You'll get a framework/app/api that will deliver you the info programmed by someone really into AI. It'll be business as usual. Know API's, frameworks, how to analyse data and tools around this, know people. AKA Just be a good programmer.
However, the author of this thread I don't think was asking how to go about implementing someone's API as much as how to be the one to create the AIs that the APIs in the future might attach to.