
6.S094: Deep Learning for Self-Driving Cars - tancik
http://cars.mit.edu
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Animats
Trying to do self-driving entirely by deep learning in a reactive system seems
like a terrible idea. Deep learning to classify objects (bicycles,
pedestrians, cars, traffic lights, telephone poles, cops) is fine. But map
building, planning, and obstacle avoidance needs to be more reliable than a
purely reactive system can do.

Look at the videos from Urmson's talk at SXSW. That shows the worldview of a
Google self-driving car. It's about 80% geometry and 20% classification.

Yes, you can get a pure deep learning system to drive on a freeway. But how
does it do in a more cluttered environment? A system that builds local maps
and profiles terrain with LIDAR can deal with clutter.

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tabeth
Why exactly can't you use deep learning to drive in a "cluttered environment?"
You didn't mention why it's a terrible idea (I have no background in deep
learning, just curious)

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hackernewsacct
What are good online sources for a beginner to learn calculus, linear algebra
and stats/probability needed for machine learning?

I don't want courses that teach math by coding but actual math courses. A lot
of these online ML courses treat math as a black box so you never fully
understand what's going on & a lot of math based ML courses are too advanced.

So I'd rather focus on understanding the math basics before diving into ML. So
what do you guys recommend?

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tsomctl
Calculus, by James Stewart. I recommend you buy a dead tree copy of an old
edition (I paid $5 for mine, shipped. I don't know how they made money off
that sale.) Might not be the best book, but it covers everything you need to
know, has good exercises, everyone uses it, you can find the solutions manual
online, and the harder problems have an answer on stack overflow.

And some linear algebra book by Strang (as others have said.) I don't remember
which one I learned from, but I do remember it was excellent.

I can't recommend a good stats/probability book. People recommend Statistical
Inference by Casella and Berger, although I wasn't super impressed with it.

You'll also want a good understanding of set theory and proof writing. I don't
remember what book I learned from, but try to find some introduction to math
thought.

This is all assuming you have a good understanding of algebra. The above
mentioned books require geometry/trig, but you don't actually need that for
machine learning.

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physicsyogi
I'd also recommend _Calculus for the Practical Man_. It's what Feynman used
and is quite good for learning how to calculate various things with calculus.

Incidentally, my college calculus class also used Stewart.

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randcraw
BTW, there's a well regarded new book on autonomous cars that looks like fun:
'Driverless: Intelligent Cars and the Road Ahead' by Lipson and Kurman. Lipson
is a professor of robotics at Columbia.

[https://www.amazon.com/gp/product/0262035227/ref=oh_aui_deta...](https://www.amazon.com/gp/product/0262035227/ref=oh_aui_detailpage_o07_s00?ie=UTF8&psc=1)

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throwthrow222
Which specific Coursera and/or Udacity courses are good for coming up to speed
on the math/stats&probability knowledge needed for their SDC/AI/ML courses?

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krastanov
A linear algebra course is the bare minimum (and frequently it can be enough).
You can pick up any textbook and that would give you good enough preparation.

After that you probably will have enough domain knowledge to choose what
course to take next yourself.

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monocasa
If I don't really remember what all was in my Linear Algebra class from 15
years ago, but have a working knowledge from graphics would that work, or
would I need more of a theoretical background in linear algebra do you think?

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buckhx
It looks like they'll be posting the lectures online which is pretty rad. I'll
be sure to make some time to watch these.

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gravypod
I was reading through the page on the Docker install [0] and after giving it a
look I'm really interested in a docker GUI. I'd hate to have to type or
memorize that for a class or for doing something useful and I'd also dislike
needing to maintain a file with 50 different scripts to stop & start docker
and what I want to run at any given time.

Anyone know of something like that?

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zerr
I wonder how it compares to Udacity's similar course.

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deepnotderp
IMO, the udacity SDC course is pretty bad.

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kyle_martin1
I just enrolled in the Udacity SDC nanodegree. Can you elaborate?

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bitL
It's pretty cool, you'll have fun! It's "practical" not "theoretical", so the
focus is on getting code working and understanding bare minimum of math you
need.

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kyle_martin1
Sounds pretty similar to Udacity's AI for Robots course! Good to know that
they focus on intuition rather than rigor. Many professor enjoy stroking their
ego with rigorous math, rather than communicating higher-level ideas and
making their subject seem "easy".

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windsignaling
That perspective seems a little naive.

They are professionals, so they know "what it takes" to be good at the
subject.

Machine learning math is not rigorous in comparison to the type of math you'd
study as a math or physics major.

Machine learning math is useful precisely because of the fact that it shows
you intuitively how the concepts work.

Knowing the "high level" ideas is near-useless. I can get the "high level"
ideas of quantum mechanics from any high school or pop science physics book.
Does that mean I know quantum mechanics? Only at an extremely superficial
level.

And I suspect anyone taking a MOOC on AI or machine learning wants to end up
with more than superficial knowledge.

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kyle_martin1
Sorry I wasn't clear about "high level".

I was mostly speaking about math professors in college. I have degrees in Math
and EE...advance math isn't an issue.

Having abstract intuition (aka "high level ideas") in math is incredibly
value.

Sometimes things get hairy in the computation and you need to step back and
consider the bigger picture again.

If you don't understand how the math works then you don't have the intuition
and vice-vera.

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shoshin23
super cool to see this here. do the lecture videos go up the same day as the
lectures?

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tancik
They should be posted within a few days of the lecture.

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joshsyn
It irks me, that this site is not using HTTPS. And wants me to register using
passwords

