best first Intro into

>>7957067
anything by JP Den Hartog.

File: sedra.jpg (36KB, 400x500px) Image search: [Google]

36KB, 400x500px

>>7957073

Electricity and Magnetism - Purcell
Classical Mechanics - Taylor
Quantum Mechanics - none
Thermodynamics - none
Fluid Dynamics - Acheson
Relativity - Carroll

ODE - Tenenbaum
PDE - Farlow
Fourier - Brown and Churchill
Complex Variables - Brown and Churchill, Ablowitz, Needham, all good
Proofs - Velleman
Set Theory - Halmos, though Velleman covers a bit
Real Analysis - Abbott, Tao, Rudin all good in increasing difficulty
Complex Analysis - Newman
Linear Algebra - Axler
Abstract Algebra - Dummit and Foote
Topology - Munkres
Differential Geometry - Kuhel

I'm still an undergrad so I don't specialize in anything but I've read through most of those and can vouch

>>7957101
>I'm still an undergrad
>I've read through most of those
<doubtful>

>>7957114
well I'm about to graduate with a physics/math double major soooo

the ones I have not read are Dummit & Foote, Munkres, Newman, Rudin, and B&C fourier but from what I've seen those are staples at most places so I don't feel bad recommeding them

>>7957067
Intro to programming C++ - Bjarne

>>7957101
>Complex Variables - Brown and Churchill, Ablowitz, Needham, all good
so you've read 3 different books on just complex variables? not even complex analysis, you needed three on just complex variables.
>Proofs - Velleman
>Set Theory - Halmos
set theory? really? although I accept halmos is babbies set theory so it's possible but the material in this book you must have covered several times over.
>Real Analysis - Abbott, Tao
two different books on real analysis?
>Linear Algebra - Axler
you didn't care about decomposition?

>>7957156
yes to all of your questions, apparently

>>7957156
Somebody really needs to write a new standard rigrous linear algebra text for undergrads.

Axler's approach is a little funky; determinants are important and they should be taught. Not just as a "here they are for completeness but never use them."

Hoffman+Kunze is still a good book but it's aging. Not a fossil yet, but it'll get there eventually.

>>7957262
what about lax? I've only done applied linalg because I'm an EE but I'm looking to get a firmer grounding in it and was considering lax (also it has a solutions manual).

>>7957276
I can't judge quality because I haven't done more than flip through Lax briefly, but it's a graduate textbook. I doubt even very strong undergrads would be able to use it as an introduction. It flies over more than what you'd see in a first semester linear algebra in like 50 pages.

>>7957156
>two different books on real analysis?
You make that sound like a bad and abnormal thing.

>you didn't care about decomposition?
Axler is a great book, decompositions are trivial and tedious.

>>7957287
>it's a graduate textbook
I don't think the pace is a problem. As I said I already have the basics down and I prefer textbooks that cover ground quickly (I actually enjoyed rudin).

>>7957262
What about shilov guys?

>>7957427
that, too. that book is basically like if gates, bezos, musk, and steve jobs wrote a book on entrepreneurship

the computability book by sipser is great too

>>7957067
>a best first Intro into textbook
Linear Algebra. Step by step.

>>7957067
Lang's Algebra is a very good introduction to the field.

>>7957370
Shilov might be a little too high octane for a true first book.

>>7957445
Agree on Sipser. You might find it lacking in certain respects if you've already taken a course, but it's great as an intro before, or if you're only interested in the subject as a dilettante.

>>7958104
Really? It might depend on where you're coming from though. For a CS undergrad, it should be fine, for a biologist, it might be overwhelming.

>>7958480
Bumping for more CS stuff ( machine learning and ai please)

>>7959048
http://4chan-science.wikia.com/wiki/Computer_Science_and_Engineering#AI.2C_Machine_Learning.2C_and_Computer_Vision

>>7959048
Russell and Norvig for general AI.
For ML, not sure. Again, might depend on where you're coming from. Check out 'The Elements of Statistical Learning' and 'An Introduction To Statistical Learning with Appliacations in R'. They're basically the same, but the latter is more geared towards the applied part, obv.

File: 292079.jpg (19KB, 318x454px) Image search: [Google]

19KB, 318x454px

>>7957067
Dont come to me with Tao. Best intro pic related

>>7957101
>Quantum Mechanics - none
>Thermodynamics - none
Lol, why even list these if you don't have a recommendation?

>>7959318
Tao and Rudin seem like they serve different purposes though. I know Tao used both when he taught the course, but his book seems more like it would be useful as an intro proofs 'with motivation' book.

>>7959332
Recommend then