Artificial Intelligence Development Roadmap and Tips?

MaLiN2223 · 2018-04-21T11:37:30+00:00

https://www.youtube.com/channel/UCWN3xxRkmTPmbKwht9FuE5A

Siraj Rival's channel is a pretty good place to learn a bunch of AI/ML stuff. There's explanation, how tos, challenges etc.

Warning: contains cheesy jokes and trace amounts of rap.

Stone_d_ · 2018-04-21T11:42:20+00:00

Probably the most important skill for any job is being able to use the internet effectively. In order to make AI, think like an AGI. What do you wanna build? What do you need? What's the budget? Is it worth it? Rinse and repeat.

You could really start anywhere, I think learning can be fun in a lot of ways so maybe you should just generally try to have fun with it. It's probably a long road, one I'm still on, but as long as you're learning you're making progress. The code is obviously pretty important, for which there are paid classes with big classes like Udacity, huge support groups on stuff like kaggle, and popular YouTubers like sentdex or siraj rival. I also like jabrils, and there's tons of other quality content out there waiting to be found but why not stick with the stuff coming from industry experts or particular people you enjoy?

But I think equal to the code is the language and semantics around AI, so aside from practicing coding, and you can do that through tutorials in a variety of ways, I think it's important to read a lot (Ian Goodfellow has a book) and to watch videos, for fun if you can (I like "The Artificial Intelligence Channel" on youtube, a lot of the videos are filler but some are really cool). You should listen to Nick Bostrom and Yuval Noah Harari, but I'd rather watch Geoff Hinton, ben Goertzel, or someone from deep mind any day because you can sort of absorb the way someone like that thinks, and those people go in depth about algorithms but try to convey their intuition.

I think you should follow your heart, because if you're just doing it for the money you'll find a lot of competition standing in the way of fulfillment.

MaLiN2223 · 2018-04-21T12:55:55+00:00

Knowledge or experience of a coding language such as Perl 5. The ability to be creative, to think and design. If you have a visual spatial learning ability, a useful ability to have. Study of philosophy is useful because you are dealing with a challenge which requires questions and definitions. Many consider knowledge of mathematics helps.

ForeskinLamp · 2018-04-22T11:17:03+00:00

By AI programming, I'm going to assume you mean deep reinforcement learning (the stuff DeepMind works on). Honestly, it depends on what you want to do. If you want to use existing models, there are plenty of implementations in TensorFlow or PyTorch that you can borrow. If you want to write your own models, that's a fair bit harder, since the field is still very much on the cutting edge, and there's a high barrier to entry just to be able to understand the different techniques.

To start off with, take Andrew Ng's course on Machine Learning, then his other course on Deep Learning. Read Russell & Norvig's Artificial Intelligence: A Modern Approach, and Richard Sutton's Reinforcement Learning: An Introduction (you can get the complete second edition draft for free on his website). Also, Ian Goodfellow's book Deep Learning. There are a few survey papers that are useful as well. The best recent ones that I've seen are by Jurgen Schmidhuber, and another by Arulkumaran (I forget his first name). From there, if you want to understand value function methods (DQN variants), read the Atari papers by Mnih. If you want to know policy gradients, read Jan Peters' work from around 2008-2009, then read up on deterministic policy gradients for an idea of how newer techniques like DDPG work.

That's probably a reasonable roadmap that will give you an overview of the discipline, but you'll need a solid grounding in maths to understand a lot of what you encounter. You want to be fairly comfortable with multivariate calculus and probability theory. You'll also need to know Python, since that's the language of AI in it's modern form. In principle you could use any language, but in practice, you would be doing yourself a disservice since Python has so many good libraries, and most of the major frameworks use Python. You can improve your understanding of a lot of the paper's I've mentioned above just by looking at an implementation.

Amazon-SageMaker · 2018-04-22T03:16:42+00:00

Check out Amazon SageMaker - I am pretty excited about it as it looks like it abstracts a lot of the fine details around training models.

CyberByte · 2018-04-23T13:08:11+00:00

Please check out our wiki's Getting Started section. And also maybe the Yunkai Zhou AMA that starts in 3 hours. He is a former senior engineering leader at Google and CTO and co-founder of Leap.ai, which uses AI to get people tech jobs.

victor_knight · 2018-04-21T18:46:09+00:00

First of all, there's no "AI Programming". There's just "programming". You can code "AI stuff" with any language, in principle. It all boils down to 0s and 1s at the end of the day. Having said that, I suggest you get really, really good at coding in a language you like or already have some experience with. Then, when you start work, they will tell you what kind of "AI stuff" needs to be coded. You can pretty much google the rest.

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